We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement ti...We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.展开更多
Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,huma...Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.展开更多
Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was propose...Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.展开更多
The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eas...The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eastern region of North Kivu,has been deteriorating.The study was anchored in social identity theory.The research methodology employed for this study was qualitative,focusing on the analysis of Mr.Edgar Mateso’s contributions to Radio Okapi’s“Dialogue entre Congolais”program during the period from 2019 to 2023.The research was conducted within the broader context of the persistent war and conflict in the Democratic Republic of Congo,providing valuable insights into the dynamics and challenges of addressing the ongoing insecurity and violence in the region.The study found that media,exemplified by Radio Okapi,plays a multifaceted and significant role in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo(DRC).It serves as a critical source of accurate information,enabling informed decision-making regarding ceasefire agreements,peace talks,and humanitarian aid.Media fosters dialogue and understanding among different stakeholders,contributing to reconciliation efforts.Additionally,it raises awareness about the human cost of the conflict,challenges misinformation,monitors peace agreements,amplifies the concerns of the affected population,and promotes human rights and justice.Media also engages youth,serves as an early warning system,and attracts global attention to the conflict.It is recommended that media organizations in North Kivu continue their efforts to facilitate dialogue and understanding among different stakeholder groups.Additionally,media should maintain its focus on raising awareness about the human cost of the conflict,ensuring that the suffering of civilians remains in the spotlight and generates international empathy and support.Media outlets should also continue their role as watchdogs by closely monitoring the implementation of ceasefire agreements and reporting any violations transparently.To strengthen media’s role in promoting peace,there should be continued advocacy for peace through dedicated radio programs,news reports,and editorial content.Internationally,media should continue to provide comprehensive coverage of the conflict in North Kivu,attracting global attention and shaping the perception of the conflict on the global stage.Lastly,media organizations should preserve a lasting legacy of peace by archiving peace-related content,documentaries,and narratives of reconciliation.展开更多
Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrat...Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.展开更多
Super-resolution(SR)microscopy has dramatically enhanced our understanding of biological processes.However,scattering media in thick specimens severely limits the spatial resolution,often rendering the images unclear ...Super-resolution(SR)microscopy has dramatically enhanced our understanding of biological processes.However,scattering media in thick specimens severely limits the spatial resolution,often rendering the images unclear or indistinguishable.Additionally,live-cell imaging faces challenges in achieving high temporal resolution for fast-moving subcellular structures.Here,we present the principles of a synthetic wave microscopy(SWM)to extract three-dimensional information from thick unlabeled specimens,where photobleaching and phototoxicity are avoided.SWM exploits multiple-wave interferometry to reveal the specimen’s phase information in the area of interest,which is not affected by the scattering media in the optical path.SWM achieves~0.42λ/NA resolution at an imaging speed of up to 106 pixels/s.SWM proves better temporal resolution and sensitivity than the most conventional microscopes currently available while maintaining exceptional SR and anti-scattering capabilities.Penetrating through the scattering media is challenging for conventional imaging techniques.Remarkably,SWM retains its efficacy even in conditions of low signal-to-noise ratios.It facilitates the visualization of dynamic subcellular structures in live cells,encompassing tubular endoplasmic reticulum(ER),lipid droplets,mitochondria,and lysosomes.展开更多
Purpose:Our study aims to compare speech understanding in noise and spectral-temporal resolution skills with regard to the degree of hearing loss,age,hearing aid use experience and gender of hearing aid users.Methods:...Purpose:Our study aims to compare speech understanding in noise and spectral-temporal resolution skills with regard to the degree of hearing loss,age,hearing aid use experience and gender of hearing aid users.Methods:Our study included sixty-eight hearing aid users aged between 40-70 years,with bilateral mild and moderate symmetrical sensorineural hearing loss.Random gap detection test,Turkish matrix test and spectral-temporally modulated ripple test were implemented on the participants with bilateral hearing aids.The test results acquired were compared statistically according to different variables and the correlations were examined.Results:No statistically significant differences were observed for speech-in-noise recognition,spectraltemporal resolution among older and younger adults in hearing aid users(p>0.05).There wasn’t found a statistically significant difference among test outcomes as regards different hearing loss degrees(p>0.05).Higher performances were obtained in terms of temporal resolution in male participants and participants with more hearing aid use experience(p<0.05).Significant correlations were obtained between the results of speech-in-noise recognition,temporal resolution and spectral resolution tests performed with hearing aids(p<0.05).Conclusion:Our study findings emphasized the importance of regular hearing aid use and it showed that some auditory skills can be improved with hearing aids.Observation of correlations among the speechin-noise recognition,temporal resolution and spectral resolution tests have revealed that these skills should be evaluated as a whole to maximize the patient’s communication abilities.展开更多
Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applicati...Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applications.Recently,thermal neutron radiography experiments based on a D-T neutron generator performed by Hefei Institutes of Physical Science indicated a significant resolution deviation between the experimental results and the values calculated using the traditional resolution model.The experimental result was up to 23%lower than the calculated result,which hinders the achievement of the design goal of a compact neutron radiography system.A GEANT4 Monte Carlo code was developed to simulate the CTNR process,aiming to identify the key factors leading to resolution deviation.The effects of a low collimation ratio and high-energy neutrons were analyzed based on the neutron beam environment of the CTNR system.The results showed that the deviation was primarily caused by geometric distortion at low collimation ratios and radiation noise induced by highenergy neutrons.Additionally,the theoretical model was modified by considering the imaging position and radiation noise factors.The modified theoretical model was in good agreement with the experimental results,and the maximum deviation was reduced to 4.22%.This can be useful for the high-precision design of CTNR systems.展开更多
Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with diffe...Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with different spatial resolutions,which leads to different results in tuna fishery prediction.Study on the impact of different spatial resolutions on the prediction accuracy of albacore tuna fishery to select the best spatial resolution can contribute to better management of albacore tuna resources.The nominal catch per unit effort(CPUE)of albacore tuna is calculated according to vessel monitor system(VMS)data collected from Chinese distantwater fishery enterprises from January 1,2017 to May 31,2021.A total of 26 spatiotemporal and environmental factors,including temperature,salinity,dissolved oxygen of 0–300 m water layer,chlorophyll-a concentration in the sea surface,sea surface height,month,longitude,and latitude,were selected as variables.The temporal resolution of the variables was daily and the spatial resolutions were set to be 0.5°×0.5°,1°×1°,2°×2°,and 5°×5°.The relationship between the nominal CPUE and each individual factor was analyzed to remove the factors irrelavant to the nominal CPUE,together with a multicollinearity diagnosis on the factors to remove factors highly related to the other factors within the four spatial resolutions.The relationship models between CPUE and spatiotemporal and environmental factors by four spatial resolutions were established based on the long short-term memory(LSTM)neural network model.The mean absolute error(MAE)and root mean square error(RMSE)were used to analyze the fitness and accuracy of the models,and to determine the effects of different spatial resolutions on the prediction accuracy of the albacore tuna fishing ground.The results show the resolution of 1°×1°can lead to the best prediction accuracy,with the MAE and RMSE being 0.0268 and 0.0452 respectively,followed by 0.5°×0.5°,2°×2°and 5°×5°with declining prediction accuracy.The results suggested that 1)albacore tuna fishing ground can be predicted by LSTM;2)the VMS records the data in detail and can be used scientifically to calculate the CPUE;3)correlation analysis,and multicollinearity diagnosis are necessary to improve the prediction accuracy of the model;4)the spatial resolution should be 1°×1°in the forecast of albacore tuna fishing ground in waters near the Cook Islands.展开更多
The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark sour...The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.展开更多
The introduction of living cells to manufacturing process has enabled the engineering of complex biological tissues in vitro.The recent advances in biofabrication with extremely high resolution(e.g.at single cell leve...The introduction of living cells to manufacturing process has enabled the engineering of complex biological tissues in vitro.The recent advances in biofabrication with extremely high resolution(e.g.at single cell level)have greatly enhanced this capacity and opened new avenues for tissue engineering.In this review,we comprehensively overview the current biofabrication strategies with single-cell resolution and categorize them based on the dimension of the single-cell building blocks,i.e.zero-dimensional single-cell droplets,one-dimensional single-cell filaments and two-dimensional single-cell sheets.We provide an informative introduction to the most recent advances in these approaches(e.g.cell trapping,bioprinting,electrospinning,microfluidics and cell sheets)and further illustrated how they can be used in in vitro tissue modelling and regenerative medicine.We highlight the significance of single-cell-level biofabrication and discuss the challenges and opportunities in the field.展开更多
We develop an x-ray Ti/Au transition-edge sensor(TES)with an Au absorber deposited on the center of TES and improved its energy resolution using the K-means clustering algorithm in combination with Wiener filter.We fi...We develop an x-ray Ti/Au transition-edge sensor(TES)with an Au absorber deposited on the center of TES and improved its energy resolution using the K-means clustering algorithm in combination with Wiener filter.We firstly extract the main parameters of each recorded pulse trace,which are adopted to classify these traces into several clusters in the K-means clustering algorithm.Then real traces are selected for energy resolution analysis.Following the baseline correction,the Wiener filter is used to improve the signal-to-noise ratio.Although the silicon underneath the TES has not been etched to reduce the thermal conductance,the energy resolution of the developed x-ray TES is improved from 94 eV to 44 eV at 5.9 keV.展开更多
Additive manufacturing(AM)is a free-form technology that shows great potential in the integrated creation of three-dimensional(3D)electronics.However,the fabrication of 3D conformal circuits that fulfill the requireme...Additive manufacturing(AM)is a free-form technology that shows great potential in the integrated creation of three-dimensional(3D)electronics.However,the fabrication of 3D conformal circuits that fulfill the requirements of high service temperature,high conductivity and high resolution remains a challenge.In this paper,a hybrid AM method combining the fused deposition modeling(FDM)and hydrophobic treatment assisted laser activation metallization(LAM)was proposed for manufacturing the polyetheretherketone(PEEK)-based 3D electronics,by which the conformal copper patterns were deposited on the 3D-printed PEEK parts,and the adhesion between them reached the 5B high level.Moreover,the 3D components could support the thermal cycling test from-55℃ to 125℃ for more than 100 cycles.Particularly,the application of a hydrophobic coating on the FDM-printed PEEK before LAM can promote an ideal catalytic selectivity on its surface,not affected by the inevitable printing borders and pores in the FDM-printed parts,then making the resolution of the electroless plated copper lines improved significantly.In consequence,Cu lines with width and spacing of only60μm and 100μm were obtained on both as-printed and after-polished PEEK substrates.Finally,the potential of this technique to fabricate 3D conformal electronics was demonstrated.展开更多
The excellent remote sensing ability of synthetic aperture radar(SAR)will be misled seriously when it encounters deceptive jamming which possesses high fidelity and fraudulence.In this paper,the dynamic synthetic aper...The excellent remote sensing ability of synthetic aperture radar(SAR)will be misled seriously when it encounters deceptive jamming which possesses high fidelity and fraudulence.In this paper,the dynamic synthetic aperture(DSA)scheme is used to extract the difference between the true and false targets.A simultaneous deceptive jamming suppression and target reconstruction method is proposed for a single channel SAR system to guarantee remote sensing ability.The system model is formulated as a sparse signal recovery problem with an unknown parametric dictionary to be estimated.An iterative reweighted method is employed to jointly handle the dictionary parameter learning and target reconstruction problem in an majorization-minimization framework,where a surrogate function majorizing the Gaussian entropy in the objective function is introduced to circumvent its non-convexity.After dictionary parameter learning,the grid mismatching problem in a fixed grid based method is avoided.Therefore,the proposed method can reap a super resolution result.Besides,a simple yet effective DSA section scheme is developed for the SAR data excerpting,in which only two DSAs are required.Experimental results about location error and reconstruction power error reveal that the proposed method is able to achieve a good performance in deceptive jamming suppression.展开更多
Extrusion-based cell deposition has become a prominent technique for expanding bioprinting applications.However,the associated print resolution in the order of nanolitre or above has been a limiting factor.The demand ...Extrusion-based cell deposition has become a prominent technique for expanding bioprinting applications.However,the associated print resolution in the order of nanolitre or above has been a limiting factor.The demand for improving print resolution towards the scale of a single cell has driven the development of precision nozzle extrusion,although the benefits gained remain ambiguous.Here,aided by in situ imaging,we investigated the dynamics of cell organisation through an extrusion-based microcapillary tip with picolitre precision through in-air or immersion deposition.The microcapillary extrusion setup,termed‘Picodis’,was demonstrated by generating droplets of colouring inks immersed in an immiscible medium.Next,using 3T3 fibroblast cells as an experimental model,we demonstrated the deposition of cell suspension,and pre-aggregated cell pellets.Then,the dynamic organisation of cells within the microcapillary tip was described,along with cell ejection and deposition upon exiting the tip opening.The vision-assisted approach revealed that when dispersed in a culture medium,the movements of cells were distinctive based on the flow profiles and were purely driven by laminar fluid flow within a narrow tip.The primary process limitations were cell sedimentation,aggregation and compaction,along with trapped air bubbles.The use of picolitre-level resolution microcapillary extrusion,although it provides some level of control for a small number of cells,does not necessarily offer a reliable method when a specified number of cells are required.Our study provides insights into the process limitations of high-resolution cell ink extrusion,which may be useful for optimising biofabrication processes of cell-laden constructs for biomedical research.展开更多
Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancem...Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancement methods are difficult to yield satisfactory processing outcomes for reservoir characterization. To solve this problem, we develop a new approach for simultaneous denoising and resolution enhancement of seismic data based on convolution dictionary learning. First, an elastic convolution dictionary learning algorithm is presented to efficiently learn a convolution dictionary with stronger representation capability from the noisy data to be processed. Specifically, the algorithm introduces the elastic L1/2 norm as a sparsity constraint and employs a steepest gradient descent strategy to efficiently solve the frequency-domain linear system with substantial computational cost in a half-quadratic splitting framework. Then, based on the learned convolution dictionary, a weighted convolutional sparse representation paradigm is designed to encode the noisy data to acquire an optimal sparse approximation of the effective signal. Subsequently, a high-resolution dictionary with a broadband spectrum is constructed by the proposed parameter scaling strategy and matched filtering technique on the basis of atomic spectrum modeling. Finally, the optimal sparse approximation of the effective signal and the constructed high-resolution dictionary are used for data reconstruction to obtain the seismic signal with high resolution and high signal-to-noise ratio. Synthetic and field dataset examples are executed to check the effectiveness and reliability of the developed method. The results indicate that this method has a more competitive performance in seismic applications compared with the conventional deconvolution and spectral whitening methods.展开更多
Single image super resolution(SISR)techniques produce images of high resolution(HR)as output from input images of low resolution(LR).Motivated by the effectiveness of deep learning methods,we provide a framework based...Single image super resolution(SISR)techniques produce images of high resolution(HR)as output from input images of low resolution(LR).Motivated by the effectiveness of deep learning methods,we provide a framework based on deep learning to achieve super resolution(SR)by utilizing deep singular-residual neural network(DSRNN)in training phase.Residuals are obtained from the difference between HR and LR images to generate LR-residual example pairs.Singular value decomposition(SVD)is applied to each LR-residual image pair to decompose into subbands of low and high frequency components.Later,DSRNN is trained on these subbands through input and output channels by optimizing the weights and biases of the network.With fewer layers in DSRNN,the influence of exploding gradients is reduced.This speeds up the learning process and also improves accuracy by using skip connections.The trained DSRNN parameters yield residuals to recover the HR subbands in the testing phase.Experimental analysis shows that the proposed method results in superior performance to existingmethods in terms of subjective quality.Extensive testing results on popular benchmark datasets such as set5,set14,and urban100 for a scaling factor of 4 show the effectiveness of the proposed method across different qualitative evaluation metrics.展开更多
High-resolution medical images have important medical value,but are difficult to obtain directly.Limited by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is of...High-resolution medical images have important medical value,but are difficult to obtain directly.Limited by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is often not high.Therefore,many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical images.However,current super-resolution algorithms only work on a single scale,and multiple networks need to be trained when super-resolution images of different scales are needed.This definitely raises the cost of acquiring high-resolution medical images.Thus,we propose a multi-scale superresolution algorithm using meta-learning.The algorithm combines a metalearning approach with an enhanced depth of residual super-resolution network to design a meta-upscale module.The meta-upscale module utilizes the weight prediction property of meta-learning and is able to perform the super-resolution task of medical images at any scale.Meanwhile,we design a non-integer mapping relation for super-resolution,which allows the network to be trained under non-integer magnification requirements.Compared to the state-of-the-art single-image super-resolution algorithm on computed tomography images of the pelvic region.The meta-learning multiscale superresolution algorithm obtained a surpassing of about 2%at a smaller model volume.Testing on different parts proves the high generalizability of our algorithm.Multi-scale super-resolution algorithms using meta-learning can compensate for hardware device defects and reduce secondary harm to patients while obtaining high-resolution medical images.It can be of great use in imaging related fields.展开更多
We propose a single-pixel imaging(SPI)method to achieve a higher-resolution image via the Hadamard transform matrix.Unlike traditional SPI schemes,this new method recovers images by correlating single-pixel signals wi...We propose a single-pixel imaging(SPI)method to achieve a higher-resolution image via the Hadamard transform matrix.Unlike traditional SPI schemes,this new method recovers images by correlating single-pixel signals with synchronized transformed patterns of Hadamard bases that are actually projected onto the digital micromirror device.Each transform pattern is obtained through the inverse Fourier transform of the pattern acquired by Gaussian filtering of each Hadamard basis in the frequency domain.The proposed scheme is based on a typical SPI experimental setup and does not add any hardware complexity,enabling the transformation of Hadamard matrices and image reconstruction through data processing alone.Therefore,this approach could be considered as an alternative option for achieving fast SPI in a diffraction-limited imaging system,without the need for additional hardware.展开更多
Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing da...Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.展开更多
基金Project supported by the Natural Science Foundation of Shandong Province,China(Grant Nos.ZR2020MF119 and ZR2020MA082)the National Natural Science Foundation of China(Grant No.62002208)the National Key Research and Development Program of China(Grant No.2018YFB0504302).
文摘We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.
基金the National Natural Science Foundation of China(Grant Number 62076246).
文摘Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.
基金The National Key Research and Development Program of China under contract Nos 2023YFD2401900 and 2020YFD09008004the National Natural Science Foundation of China Key International(Regional)Cooperative Research Project under contract No.42020104009the Basic Public Welfare Research Program of Zhejiang Province under contract No.LGF21D010004.
文摘Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.
文摘The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eastern region of North Kivu,has been deteriorating.The study was anchored in social identity theory.The research methodology employed for this study was qualitative,focusing on the analysis of Mr.Edgar Mateso’s contributions to Radio Okapi’s“Dialogue entre Congolais”program during the period from 2019 to 2023.The research was conducted within the broader context of the persistent war and conflict in the Democratic Republic of Congo,providing valuable insights into the dynamics and challenges of addressing the ongoing insecurity and violence in the region.The study found that media,exemplified by Radio Okapi,plays a multifaceted and significant role in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo(DRC).It serves as a critical source of accurate information,enabling informed decision-making regarding ceasefire agreements,peace talks,and humanitarian aid.Media fosters dialogue and understanding among different stakeholders,contributing to reconciliation efforts.Additionally,it raises awareness about the human cost of the conflict,challenges misinformation,monitors peace agreements,amplifies the concerns of the affected population,and promotes human rights and justice.Media also engages youth,serves as an early warning system,and attracts global attention to the conflict.It is recommended that media organizations in North Kivu continue their efforts to facilitate dialogue and understanding among different stakeholder groups.Additionally,media should maintain its focus on raising awareness about the human cost of the conflict,ensuring that the suffering of civilians remains in the spotlight and generates international empathy and support.Media outlets should also continue their role as watchdogs by closely monitoring the implementation of ceasefire agreements and reporting any violations transparently.To strengthen media’s role in promoting peace,there should be continued advocacy for peace through dedicated radio programs,news reports,and editorial content.Internationally,media should continue to provide comprehensive coverage of the conflict in North Kivu,attracting global attention and shaping the perception of the conflict on the global stage.Lastly,media organizations should preserve a lasting legacy of peace by archiving peace-related content,documentaries,and narratives of reconciliation.
文摘Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.
基金support from CAS West Light Grant (xbzgzdsys-202206)National Key Research and Development Program of China (2021YFA1401003).
文摘Super-resolution(SR)microscopy has dramatically enhanced our understanding of biological processes.However,scattering media in thick specimens severely limits the spatial resolution,often rendering the images unclear or indistinguishable.Additionally,live-cell imaging faces challenges in achieving high temporal resolution for fast-moving subcellular structures.Here,we present the principles of a synthetic wave microscopy(SWM)to extract three-dimensional information from thick unlabeled specimens,where photobleaching and phototoxicity are avoided.SWM exploits multiple-wave interferometry to reveal the specimen’s phase information in the area of interest,which is not affected by the scattering media in the optical path.SWM achieves~0.42λ/NA resolution at an imaging speed of up to 106 pixels/s.SWM proves better temporal resolution and sensitivity than the most conventional microscopes currently available while maintaining exceptional SR and anti-scattering capabilities.Penetrating through the scattering media is challenging for conventional imaging techniques.Remarkably,SWM retains its efficacy even in conditions of low signal-to-noise ratios.It facilitates the visualization of dynamic subcellular structures in live cells,encompassing tubular endoplasmic reticulum(ER),lipid droplets,mitochondria,and lysosomes.
文摘Purpose:Our study aims to compare speech understanding in noise and spectral-temporal resolution skills with regard to the degree of hearing loss,age,hearing aid use experience and gender of hearing aid users.Methods:Our study included sixty-eight hearing aid users aged between 40-70 years,with bilateral mild and moderate symmetrical sensorineural hearing loss.Random gap detection test,Turkish matrix test and spectral-temporally modulated ripple test were implemented on the participants with bilateral hearing aids.The test results acquired were compared statistically according to different variables and the correlations were examined.Results:No statistically significant differences were observed for speech-in-noise recognition,spectraltemporal resolution among older and younger adults in hearing aid users(p>0.05).There wasn’t found a statistically significant difference among test outcomes as regards different hearing loss degrees(p>0.05).Higher performances were obtained in terms of temporal resolution in male participants and participants with more hearing aid use experience(p<0.05).Significant correlations were obtained between the results of speech-in-noise recognition,temporal resolution and spectral resolution tests performed with hearing aids(p<0.05).Conclusion:Our study findings emphasized the importance of regular hearing aid use and it showed that some auditory skills can be improved with hearing aids.Observation of correlations among the speechin-noise recognition,temporal resolution and spectral resolution tests have revealed that these skills should be evaluated as a whole to maximize the patient’s communication abilities.
基金supported by the Nuclear Energy Development Project of China (No.[2019]1342)the Presidential Foundation of HFIPS (No.YZJJ2022QN40)。
文摘Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applications.Recently,thermal neutron radiography experiments based on a D-T neutron generator performed by Hefei Institutes of Physical Science indicated a significant resolution deviation between the experimental results and the values calculated using the traditional resolution model.The experimental result was up to 23%lower than the calculated result,which hinders the achievement of the design goal of a compact neutron radiography system.A GEANT4 Monte Carlo code was developed to simulate the CTNR process,aiming to identify the key factors leading to resolution deviation.The effects of a low collimation ratio and high-energy neutrons were analyzed based on the neutron beam environment of the CTNR system.The results showed that the deviation was primarily caused by geometric distortion at low collimation ratios and radiation noise induced by highenergy neutrons.Additionally,the theoretical model was modified by considering the imaging position and radiation noise factors.The modified theoretical model was in good agreement with the experimental results,and the maximum deviation was reduced to 4.22%.This can be useful for the high-precision design of CTNR systems.
基金the National Natural Science Foundation of China(No.32273185)the National Key R&D Program of China(No.2020YFD0901205)the Marine Fishery Resources Investigation and Exploration Program of the Ministry of Agriculture and Rural Affairs of China in 2021(No.D-8006-21-0215)。
文摘Albacore tuna(Thunnus alalunga)is one of the target species of tuna longline fishing,and waters near the Cook Islands are a vital albacore tuna fishing ground.Marine environmental data are usually presented with different spatial resolutions,which leads to different results in tuna fishery prediction.Study on the impact of different spatial resolutions on the prediction accuracy of albacore tuna fishery to select the best spatial resolution can contribute to better management of albacore tuna resources.The nominal catch per unit effort(CPUE)of albacore tuna is calculated according to vessel monitor system(VMS)data collected from Chinese distantwater fishery enterprises from January 1,2017 to May 31,2021.A total of 26 spatiotemporal and environmental factors,including temperature,salinity,dissolved oxygen of 0–300 m water layer,chlorophyll-a concentration in the sea surface,sea surface height,month,longitude,and latitude,were selected as variables.The temporal resolution of the variables was daily and the spatial resolutions were set to be 0.5°×0.5°,1°×1°,2°×2°,and 5°×5°.The relationship between the nominal CPUE and each individual factor was analyzed to remove the factors irrelavant to the nominal CPUE,together with a multicollinearity diagnosis on the factors to remove factors highly related to the other factors within the four spatial resolutions.The relationship models between CPUE and spatiotemporal and environmental factors by four spatial resolutions were established based on the long short-term memory(LSTM)neural network model.The mean absolute error(MAE)and root mean square error(RMSE)were used to analyze the fitness and accuracy of the models,and to determine the effects of different spatial resolutions on the prediction accuracy of the albacore tuna fishing ground.The results show the resolution of 1°×1°can lead to the best prediction accuracy,with the MAE and RMSE being 0.0268 and 0.0452 respectively,followed by 0.5°×0.5°,2°×2°and 5°×5°with declining prediction accuracy.The results suggested that 1)albacore tuna fishing ground can be predicted by LSTM;2)the VMS records the data in detail and can be used scientifically to calculate the CPUE;3)correlation analysis,and multicollinearity diagnosis are necessary to improve the prediction accuracy of the model;4)the spatial resolution should be 1°×1°in the forecast of albacore tuna fishing ground in waters near the Cook Islands.
基金Supported by the National Key R&D Program of China(No.2016YFC0303900)the Laoshan Laboratory(Nos.MGQNLM-KF201807,LSKJ202203604)the National Natural Science Foundation of China(No.42106072)。
文摘The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.
基金support from the National Natural Science Foundation of China(No.52105306,32211530075)New Faculty Start-up Funding provided by Tsinghua University(012-53330200421).
文摘The introduction of living cells to manufacturing process has enabled the engineering of complex biological tissues in vitro.The recent advances in biofabrication with extremely high resolution(e.g.at single cell level)have greatly enhanced this capacity and opened new avenues for tissue engineering.In this review,we comprehensively overview the current biofabrication strategies with single-cell resolution and categorize them based on the dimension of the single-cell building blocks,i.e.zero-dimensional single-cell droplets,one-dimensional single-cell filaments and two-dimensional single-cell sheets.We provide an informative introduction to the most recent advances in these approaches(e.g.cell trapping,bioprinting,electrospinning,microfluidics and cell sheets)and further illustrated how they can be used in in vitro tissue modelling and regenerative medicine.We highlight the significance of single-cell-level biofabrication and discuss the challenges and opportunities in the field.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12293032,120101002,12173097,and U1931123)the National Key Basic Research and Development Program of China(Grant Nos.2020YFC2201703 and 2018YFA0404701)Chinese Academy of Sciences(Grant No.GJJSTD20210002)。
文摘We develop an x-ray Ti/Au transition-edge sensor(TES)with an Au absorber deposited on the center of TES and improved its energy resolution using the K-means clustering algorithm in combination with Wiener filter.We firstly extract the main parameters of each recorded pulse trace,which are adopted to classify these traces into several clusters in the K-means clustering algorithm.Then real traces are selected for energy resolution analysis.Following the baseline correction,the Wiener filter is used to improve the signal-to-noise ratio.Although the silicon underneath the TES has not been etched to reduce the thermal conductance,the energy resolution of the developed x-ray TES is improved from 94 eV to 44 eV at 5.9 keV.
基金supported by the National Natural Science Foundation of China(Grant No.51901082)the National Postdoctoral Program for Innovative Talents(BX20200137)the National Defense Basic Scientific Research Program of China(JCKY2018110C060)。
文摘Additive manufacturing(AM)is a free-form technology that shows great potential in the integrated creation of three-dimensional(3D)electronics.However,the fabrication of 3D conformal circuits that fulfill the requirements of high service temperature,high conductivity and high resolution remains a challenge.In this paper,a hybrid AM method combining the fused deposition modeling(FDM)and hydrophobic treatment assisted laser activation metallization(LAM)was proposed for manufacturing the polyetheretherketone(PEEK)-based 3D electronics,by which the conformal copper patterns were deposited on the 3D-printed PEEK parts,and the adhesion between them reached the 5B high level.Moreover,the 3D components could support the thermal cycling test from-55℃ to 125℃ for more than 100 cycles.Particularly,the application of a hydrophobic coating on the FDM-printed PEEK before LAM can promote an ideal catalytic selectivity on its surface,not affected by the inevitable printing borders and pores in the FDM-printed parts,then making the resolution of the electroless plated copper lines improved significantly.In consequence,Cu lines with width and spacing of only60μm and 100μm were obtained on both as-printed and after-polished PEEK substrates.Finally,the potential of this technique to fabricate 3D conformal electronics was demonstrated.
基金supported in part by the National Natural Science Foundation of China under Grants 61801297,62171293,U1713217,U2033213,61971218,61801302,61701528,61601304in part by the National Science Fund for Distinguished Young Scholars under Grant 61925108+5 种基金in part by Natural Science Funding of Guangdong Province under Grant 2017A030313336in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515110509in part by Foundation of Shenzhen City under Grant JCYJ20170302142545828in part by the Shenzhen University Grant 2019119,2016057in part by the Fund of State Key Laboratory of Millimeter Waves under Grant K202235in part by Sichuan Science and Technology Program under Grant 2021YFS0319.
文摘The excellent remote sensing ability of synthetic aperture radar(SAR)will be misled seriously when it encounters deceptive jamming which possesses high fidelity and fraudulence.In this paper,the dynamic synthetic aperture(DSA)scheme is used to extract the difference between the true and false targets.A simultaneous deceptive jamming suppression and target reconstruction method is proposed for a single channel SAR system to guarantee remote sensing ability.The system model is formulated as a sparse signal recovery problem with an unknown parametric dictionary to be estimated.An iterative reweighted method is employed to jointly handle the dictionary parameter learning and target reconstruction problem in an majorization-minimization framework,where a surrogate function majorizing the Gaussian entropy in the objective function is introduced to circumvent its non-convexity.After dictionary parameter learning,the grid mismatching problem in a fixed grid based method is avoided.Therefore,the proposed method can reap a super resolution result.Besides,a simple yet effective DSA section scheme is developed for the SAR data excerpting,in which only two DSAs are required.Experimental results about location error and reconstruction power error reveal that the proposed method is able to achieve a good performance in deceptive jamming suppression.
基金supported by the European Research Council(ERC-St G,758865,to YYSH)the financial support from the W.D.Armstrong Trust and the Macao Postgraduate Scholarship Fund。
文摘Extrusion-based cell deposition has become a prominent technique for expanding bioprinting applications.However,the associated print resolution in the order of nanolitre or above has been a limiting factor.The demand for improving print resolution towards the scale of a single cell has driven the development of precision nozzle extrusion,although the benefits gained remain ambiguous.Here,aided by in situ imaging,we investigated the dynamics of cell organisation through an extrusion-based microcapillary tip with picolitre precision through in-air or immersion deposition.The microcapillary extrusion setup,termed‘Picodis’,was demonstrated by generating droplets of colouring inks immersed in an immiscible medium.Next,using 3T3 fibroblast cells as an experimental model,we demonstrated the deposition of cell suspension,and pre-aggregated cell pellets.Then,the dynamic organisation of cells within the microcapillary tip was described,along with cell ejection and deposition upon exiting the tip opening.The vision-assisted approach revealed that when dispersed in a culture medium,the movements of cells were distinctive based on the flow profiles and were purely driven by laminar fluid flow within a narrow tip.The primary process limitations were cell sedimentation,aggregation and compaction,along with trapped air bubbles.The use of picolitre-level resolution microcapillary extrusion,although it provides some level of control for a small number of cells,does not necessarily offer a reliable method when a specified number of cells are required.Our study provides insights into the process limitations of high-resolution cell ink extrusion,which may be useful for optimising biofabrication processes of cell-laden constructs for biomedical research.
基金This work is supported by the Laoshan National Laboratoryof ScienceandTechnologyFoundation(No.LSKj202203400)the National Natural Science Foundation of China(No.41874146).
文摘Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancement methods are difficult to yield satisfactory processing outcomes for reservoir characterization. To solve this problem, we develop a new approach for simultaneous denoising and resolution enhancement of seismic data based on convolution dictionary learning. First, an elastic convolution dictionary learning algorithm is presented to efficiently learn a convolution dictionary with stronger representation capability from the noisy data to be processed. Specifically, the algorithm introduces the elastic L1/2 norm as a sparsity constraint and employs a steepest gradient descent strategy to efficiently solve the frequency-domain linear system with substantial computational cost in a half-quadratic splitting framework. Then, based on the learned convolution dictionary, a weighted convolutional sparse representation paradigm is designed to encode the noisy data to acquire an optimal sparse approximation of the effective signal. Subsequently, a high-resolution dictionary with a broadband spectrum is constructed by the proposed parameter scaling strategy and matched filtering technique on the basis of atomic spectrum modeling. Finally, the optimal sparse approximation of the effective signal and the constructed high-resolution dictionary are used for data reconstruction to obtain the seismic signal with high resolution and high signal-to-noise ratio. Synthetic and field dataset examples are executed to check the effectiveness and reliability of the developed method. The results indicate that this method has a more competitive performance in seismic applications compared with the conventional deconvolution and spectral whitening methods.
文摘Single image super resolution(SISR)techniques produce images of high resolution(HR)as output from input images of low resolution(LR).Motivated by the effectiveness of deep learning methods,we provide a framework based on deep learning to achieve super resolution(SR)by utilizing deep singular-residual neural network(DSRNN)in training phase.Residuals are obtained from the difference between HR and LR images to generate LR-residual example pairs.Singular value decomposition(SVD)is applied to each LR-residual image pair to decompose into subbands of low and high frequency components.Later,DSRNN is trained on these subbands through input and output channels by optimizing the weights and biases of the network.With fewer layers in DSRNN,the influence of exploding gradients is reduced.This speeds up the learning process and also improves accuracy by using skip connections.The trained DSRNN parameters yield residuals to recover the HR subbands in the testing phase.Experimental analysis shows that the proposed method results in superior performance to existingmethods in terms of subjective quality.Extensive testing results on popular benchmark datasets such as set5,set14,and urban100 for a scaling factor of 4 show the effectiveness of the proposed method across different qualitative evaluation metrics.
基金supported by the National Science Foundation for Young Scientists of China(Grant No.61806060)2019-2021,and the Natural Science Foundation of Heilongjiang Province(LH2019F024)+1 种基金China,2019-2021.We also acknowledge support fromthe Basic andApplied Basic Research Foundation of Guangdong Province(2021A1515220140)the Youth Innovation Project of Sun Yat-sen University Cancer Center(QNYCPY32).
文摘High-resolution medical images have important medical value,but are difficult to obtain directly.Limited by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is often not high.Therefore,many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical images.However,current super-resolution algorithms only work on a single scale,and multiple networks need to be trained when super-resolution images of different scales are needed.This definitely raises the cost of acquiring high-resolution medical images.Thus,we propose a multi-scale superresolution algorithm using meta-learning.The algorithm combines a metalearning approach with an enhanced depth of residual super-resolution network to design a meta-upscale module.The meta-upscale module utilizes the weight prediction property of meta-learning and is able to perform the super-resolution task of medical images at any scale.Meanwhile,we design a non-integer mapping relation for super-resolution,which allows the network to be trained under non-integer magnification requirements.Compared to the state-of-the-art single-image super-resolution algorithm on computed tomography images of the pelvic region.The meta-learning multiscale superresolution algorithm obtained a surpassing of about 2%at a smaller model volume.Testing on different parts proves the high generalizability of our algorithm.Multi-scale super-resolution algorithms using meta-learning can compensate for hardware device defects and reduce secondary harm to patients while obtaining high-resolution medical images.It can be of great use in imaging related fields.
基金Project supported by the National Key Research and Development Program of China (Grant No.2018YFB0504302)。
文摘We propose a single-pixel imaging(SPI)method to achieve a higher-resolution image via the Hadamard transform matrix.Unlike traditional SPI schemes,this new method recovers images by correlating single-pixel signals with synchronized transformed patterns of Hadamard bases that are actually projected onto the digital micromirror device.Each transform pattern is obtained through the inverse Fourier transform of the pattern acquired by Gaussian filtering of each Hadamard basis in the frequency domain.The proposed scheme is based on a typical SPI experimental setup and does not add any hardware complexity,enabling the transformation of Hadamard matrices and image reconstruction through data processing alone.Therefore,this approach could be considered as an alternative option for achieving fast SPI in a diffraction-limited imaging system,without the need for additional hardware.
基金Under the auspices of National Key Research and Development Project of China(No.2021YFD1500103)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28100500)+2 种基金National Natural Science Foundation of China(No.4197132)Science and Technology Development Plan Project of Jilin Province(No.20210201044GX)Land Observation Satellite Supporting Platform of National Civil Space Infrastructure Project(No.CASPLOS-CCSI)。
文摘Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.
