In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based ...In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based on the combination of the single unit infrared detector.The surface dimension features of ground armored targets are identified by size calculating solution algorithm.The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target.According to the characteristics of the target signal,a custom threshold de-noising function is proposed to solve the problem of signal preprocessing.The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage.The method solves the disadvantages of wide scanning interval and low detection probability of single unit infrared detection.By reducing the scanning interval,the number of random rendezvous in the infrared feature area of the upper surface is increased,the accuracy of the size calculating is guaranteed.The experiments results show that in the fuzzy recognition method,the size calculating is introduced as the feature operator,which can improve the recognition ability of the ground armor target with different shape size.展开更多
The dynamic characteristics related to micro-motions,such as mechanical vibration or rotation, play an essential role in classifying and recognizing ballistic targets in the midcourse, and recent researches explore wa...The dynamic characteristics related to micro-motions,such as mechanical vibration or rotation, play an essential role in classifying and recognizing ballistic targets in the midcourse, and recent researches explore ways of extracting the micro-motion features from radar signals of ballistic targets. In this paper, we focus on how to investigate the micro-motion dynamic characteristics of the ballistic targets from the signals based on infrared(IR) detection, which is mainly achieved by analyzing the periodic fluctuation characteristics of the target IR irradiance intensity signatures.Simulation experiments demonstrate that the periodic characteristics of IR signatures can be used to distinguish different micromotion types and estimate related parameters. Consequently, this is possible to determine the micro-motion dynamics of ballistic targets based on IR detection.展开更多
Germanium offers many benefits over groups III-V materials when used for infrared detection. Most importantly, germanium is compatible with Complementary Metal Oxide Semiconductor (CMOS) manufacturing which allows for...Germanium offers many benefits over groups III-V materials when used for infrared detection. Most importantly, germanium is compatible with Complementary Metal Oxide Semiconductor (CMOS) manufacturing which allows for a low-cost, high-throughput device, and it does not require cooling, which many III-V devices do. With the deposition of germanium directly on silicon, there will be a thermally induced strain due to the difference in thermal expansion coefficients between the two materials. When a biaxial tensile strain is present, the direct bandgap of germanium is lowered to ~0.77 eV and is capable of absorbing longer wavelengths. We have used a two-step deposition process to create a strained germanium film in order to fabricate a photodetector device. Our device has a dark current of 1.35 nA and a photocurrent of 22.5 nA at 1570 nm wavelength. Next, we developed a model in order to compare theoretical results with experimental results. The results indicate that the model is in close agreement with our measured data, and we are therefore able to use it to model future devices.展开更多
The formations of molecular nitrogen and hydrogen complexes (η^(6)-C_(6)H_(6))Cr(CO)_(2)-L(L=N_(2) and H_(2))were observed via time-resolved infrared spectroscopy following 355 nm laser photolysis of(η^(6)-C_(6)H_(6...The formations of molecular nitrogen and hydrogen complexes (η^(6)-C_(6)H_(6))Cr(CO)_(2)-L(L=N_(2) and H_(2))were observed via time-resolved infrared spectroscopy following 355 nm laser photolysis of(η^(6)-C_(6)H_(6))Cr(CO)_(3) in the presence of N_(2) and H_(2) in gas phase.The rate constants for reactions of (η^(6)-C_(6)H_(6))Cr(CO)_(2) with N_(2) and H_(2) were measured to be(1.4±0.1)×10^(5) Torr^(-1)s^(-1) and (2.6±0.l)×10^(5) Torr^(-1)s^(-1),respectively.The complexes (η^(6)-C_(6)H_(6))Cr(CO)_(2)L(L=N_(2) and H_(2))have lifetimes longer than 1 ms in our experimental conditions implying the N_(2) and H_(2) binding energies in (η^(6)-C_(6)H_(6))Cr(CO)_(2)L,(L=N_(2) and H_(2))>17 kcal mol^(-1).展开更多
Signals from infrared detector are very weak in SO2 concentration measuring system.In order to improve the sensitivity of detection,combining with filter correlation technology and infrared absorption principle,the we...Signals from infrared detector are very weak in SO2 concentration measuring system.In order to improve the sensitivity of detection,combining with filter correlation technology and infrared absorption principle,the weak signal processing circuit is designed according to correlation detection technology.Under laboratory conditions,system performance of SO2 concentration is tested,and the experimental data are analyzed and processed.Then relationship of SO2 concentration and the measuring voltage is provided to prove that the design improves measuring sensitivity of the system.展开更多
In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted...In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).展开更多
Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means...Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.展开更多
This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden...This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden on the coast becomes a problem, both because erosion makes the cliffs unstable and because pollution increases, making the fragile dune ecosystem difficult to preserve. It is becoming necessary to increase the control of access to beaches, even if it is not a popular measure for internal and external tourism. The methodology described can also be used to monitor maritime borders. The use of images acquired in the infrared range guarantees active surveillance both day and night, the main objective being to mimic the infrared cameras already installed in some critical areas along the coastline. Using a series of infrared photographs taken at low angles with a modified camera and appropriate filter, a recent deep learning algorithm with the right training can simultaneously detect and count whole people at close range and people almost completely submerged in the water, including partially visible targets, achieving a performance with F1 score of 0.945, with 97% of targets correctly identified. This implementation is possible with ordinary laptop computers and could contribute to more frequent and more extensive coverage in beach/border surveillance, using infrared cameras at regular intervals. It can be partially automated to send alerts to the authorities and/or the nearest lifeguards, thus increasing monitoring without relying on human resources.展开更多
As a key technology for space-based Earth observation and astronomical exploration,cooled mid-wavelength and long-wavelength Infrared(IR)detection is widely used in national defense,astronomy exploration,medical imagi...As a key technology for space-based Earth observation and astronomical exploration,cooled mid-wavelength and long-wavelength Infrared(IR)detection is widely used in national defense,astronomy exploration,medical imaging,environmental monitoring,agricultural and other areas.The performances of IR detectors,including cut-off wavelength,detectivity,sensitivity and temperature resolution,plays a significant role in efficiently observing and tracking the low-temperature far-distance moving targets.Achieving optimal detection performance requires the IR detectors to operate at cryogenic temperatures.The future development of space-based applications relies heavily on the mid-wavelength and long-wavelength IR detection technologies,which should be enabled by the long-life cryogenic refrigeration and high-efficiency energy transportation system operating below 40 K,to support the Earth observation and astronomical detection.However,the efficiency degradation caused by the super low temperature brings tremendous challenges to the life time of cryogenic refrigeration and energy transportation systems.This paper evaluates the influence of cryogenic temperature on the infrared detector performances,reviews the features,development and space applications of cryogenic cooling technologies,as well as the cryogenic energy transportation approaches.Additionally,it analyzes the future development trends and challenges in supporting the space-based IR detection.展开更多
This paper proposes a real-time detection method to improve the Infrared small target detection CenterNet(ISTD-CenterNet)network for detecting small infrared targets in complex environments.The method eliminates the n...This paper proposes a real-time detection method to improve the Infrared small target detection CenterNet(ISTD-CenterNet)network for detecting small infrared targets in complex environments.The method eliminates the need for an anchor frame,addressing the issues of low accuracy and slow speed.HRNet is used as the framework for feature extraction,and an ECBAM attention module is added to each stage branch for intelligent identification of the positions of small targets and significant objects.A scale enhancement module is also added to obtain a high-level semantic representation and fine-resolution prediction map for the entire infrared image.Besides,an improved sensory field enhancement module is designed to leverage semantic information in low-resolution feature maps,and a convolutional attention mechanism module is used to increase network stability and convergence speed.Comparison experiments conducted on the infrared small target data set ESIRST.The experiments show that compared to the benchmark network CenterNet-HRNet,the proposed ISTD-CenterNet improves the recall by 22.85%and the detection accuracy by 13.36%.Compared to the state-of-the-art YOLOv5small,the ISTD-CenterNet recall is improved by 5.88%,the detection precision is improved by 2.33%,and the detection frame rate is 48.94 frames/sec,which realizes the accurate real-time detection of small infrared targets.展开更多
Infrared target detection models are more required than ever before to be deployed on embedded platforms,which requires models with less memory consumption and better real-time performance while considering accuracy.T...Infrared target detection models are more required than ever before to be deployed on embedded platforms,which requires models with less memory consumption and better real-time performance while considering accuracy.To address the above challenges,we propose a modified You Only Look Once(YOLO)algorithm PF-YOLOv4-Tiny.The algorithm incorpo-rates spatial pyramidal pooling(SPP)and squeeze-and-excitation(SE)visual attention modules to enhance the target localization capability.The PANet-based-feature pyramid networks(P-FPN)are proposed to transfer semantic information and location information simultaneously to ameliorate detection accuracy.To lighten the network,the standard convolutions other than the backbone network are replaced with depthwise separable convolutions.In post-processing the images,the soft-non-maximum suppression(soft-NMS)algorithm is employed to subside the missed and false detection problems caused by the occlusion between targets.The accuracy of our model can finally reach 61.75%,while the total Params is only 9.3 M and GFLOPs is 11.At the same time,the inference speed reaches 87 FPS on NVIDIA GeForce GTX 1650 Ti,which can meet the requirements of the infrared target detection algorithm for the embedded deployments.展开更多
Small infrared target detection has widespread applications in various fields including military,aviation,and medicine.However,detecting small infrared targets in complex backgrounds remains challenging.To detect smal...Small infrared target detection has widespread applications in various fields including military,aviation,and medicine.However,detecting small infrared targets in complex backgrounds remains challenging.To detect small infrared targets,we propose a variable-structure U-shaped network referred as CAFUNet.A central differential convolution-based encoder,ASPP,an Attention Fusion module,and a decoder module are the critical components of the CAFUNet.The encoder module based on central difference convolution effectively extracts shallow detail information from infrared images,complemented by rich contextual information obtained from the deep features in the decoder module.However,the direct fusion of the shallow detail features with semantic features may lead to feature mismatch.To address this,we incorporate an Attention Fusion(AF)module to enhance the network performance further.We performed ablation studies on each module to evaluate its effectiveness.The results show that our proposed algorithm outperforms the state-of-the-art methods on publicly available datasets.展开更多
Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This st...Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.展开更多
In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detectio...In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this paper.Firstly,the original infrared images are changed into a new infrared patch tensor mode through data reconstruction.Then,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of sparseness.Finally,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning algorithm.The test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm rate.It is a kind of infrared small and dim target detection method with good performance.展开更多
This study aimed to propose road crack detection method based on infrared image fusion technology.By analyzing the characteristics of road crack images,this method uses a variety of infrared image fusion methods to pr...This study aimed to propose road crack detection method based on infrared image fusion technology.By analyzing the characteristics of road crack images,this method uses a variety of infrared image fusion methods to process different types of images.The use of this method allows the detection of road cracks,which not only reduces the professional requirements for inspectors,but also improves the accuracy of road crack detection.Based on infrared image processing technology,on the basis of in-depth analysis of infrared image features,a road crack detection method is proposed,which can accurately identify the road crack location,direction,length,and other characteristic information.Experiments showed that this method has a good effect,and can meet the requirement of road crack detection.展开更多
Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSP...Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.展开更多
The infrared microspectroscopy beamline(BL06B) is a phase Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility(SSRF). The construction and optical alignment of BL06B were completed by the end of 2020. By...The infrared microspectroscopy beamline(BL06B) is a phase Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility(SSRF). The construction and optical alignment of BL06B were completed by the end of 2020. By 2021, it became accessible to users. The synchrotron radiation infrared(SRIR) source included edge radiation(ER) and bending magnet radiation(BMR). The extracted angles in the horizontal and vertical directions were 40 and 20 mrad, respectively. The photon flux, spectral resolution, and focused spot size were measured at the BL06B endstation, and the experimental results were consistent with theoretical calculations. SRIR light has a small divergence angle, high brightness, and a wide wavelength range. As a source of IR microscopy, it can easily focus on a diffraction-limited spatial resolution with a high signal-to-noise ratio(SNR). The BL06B endstation can be applied in a wide range of research fields, including materials, chemistry, biology, geophysics, and pharmacology.展开更多
“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the capti...“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”展开更多
Accurate classification of rice variety is essential to ensure the brand value of high-quality rice products.Considering the impact of sample state on modeling optimization algorithms,rice samples after grinding and s...Accurate classification of rice variety is essential to ensure the brand value of high-quality rice products.Considering the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were selected.To enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).展开更多
Relativistic femtosecond mid-infrared pulses can be generated efficiently by laser interaction with near-criticaldensity plasmas.It is found theoretically and numerically that the radiation pressure of a circularly po...Relativistic femtosecond mid-infrared pulses can be generated efficiently by laser interaction with near-criticaldensity plasmas.It is found theoretically and numerically that the radiation pressure of a circularly polarized laser pulse first compresses the plasma electrons to form a dense flying mirror with a relativistic high speed.The pulse reflected by the mirror is red-shifted to the mid-infrared range.Full three-dimensional simulations demonstrate that the central wavelength of the mid-infrared pulse is tunable from 3µm to 14µm,and the laser energy conversion efficiency can reach as high as 13%.With a 0.5–10 PW incident laser pulse,the generated mid-infrared pulse reaches a peak power of 10–180 TW,which is interesting for various applications in ultrafast and high-field sciences.展开更多
基金This work was supported by the National Natural Science Foundation of China(No.11804263)the Program for Innovative Science and Research Team of Xi’an Technological University.
文摘In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based on the combination of the single unit infrared detector.The surface dimension features of ground armored targets are identified by size calculating solution algorithm.The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target.According to the characteristics of the target signal,a custom threshold de-noising function is proposed to solve the problem of signal preprocessing.The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage.The method solves the disadvantages of wide scanning interval and low detection probability of single unit infrared detection.By reducing the scanning interval,the number of random rendezvous in the infrared feature area of the upper surface is increased,the accuracy of the size calculating is guaranteed.The experiments results show that in the fuzzy recognition method,the size calculating is introduced as the feature operator,which can improve the recognition ability of the ground armor target with different shape size.
文摘The dynamic characteristics related to micro-motions,such as mechanical vibration or rotation, play an essential role in classifying and recognizing ballistic targets in the midcourse, and recent researches explore ways of extracting the micro-motion features from radar signals of ballistic targets. In this paper, we focus on how to investigate the micro-motion dynamic characteristics of the ballistic targets from the signals based on infrared(IR) detection, which is mainly achieved by analyzing the periodic fluctuation characteristics of the target IR irradiance intensity signatures.Simulation experiments demonstrate that the periodic characteristics of IR signatures can be used to distinguish different micromotion types and estimate related parameters. Consequently, this is possible to determine the micro-motion dynamics of ballistic targets based on IR detection.
文摘Germanium offers many benefits over groups III-V materials when used for infrared detection. Most importantly, germanium is compatible with Complementary Metal Oxide Semiconductor (CMOS) manufacturing which allows for a low-cost, high-throughput device, and it does not require cooling, which many III-V devices do. With the deposition of germanium directly on silicon, there will be a thermally induced strain due to the difference in thermal expansion coefficients between the two materials. When a biaxial tensile strain is present, the direct bandgap of germanium is lowered to ~0.77 eV and is capable of absorbing longer wavelengths. We have used a two-step deposition process to create a strained germanium film in order to fabricate a photodetector device. Our device has a dark current of 1.35 nA and a photocurrent of 22.5 nA at 1570 nm wavelength. Next, we developed a model in order to compare theoretical results with experimental results. The results indicate that the model is in close agreement with our measured data, and we are therefore able to use it to model future devices.
基金Supported by the National Natural Science Foundation of China。
文摘The formations of molecular nitrogen and hydrogen complexes (η^(6)-C_(6)H_(6))Cr(CO)_(2)-L(L=N_(2) and H_(2))were observed via time-resolved infrared spectroscopy following 355 nm laser photolysis of(η^(6)-C_(6)H_(6))Cr(CO)_(3) in the presence of N_(2) and H_(2) in gas phase.The rate constants for reactions of (η^(6)-C_(6)H_(6))Cr(CO)_(2) with N_(2) and H_(2) were measured to be(1.4±0.1)×10^(5) Torr^(-1)s^(-1) and (2.6±0.l)×10^(5) Torr^(-1)s^(-1),respectively.The complexes (η^(6)-C_(6)H_(6))Cr(CO)_(2)L(L=N_(2) and H_(2))have lifetimes longer than 1 ms in our experimental conditions implying the N_(2) and H_(2) binding energies in (η^(6)-C_(6)H_(6))Cr(CO)_(2)L,(L=N_(2) and H_(2))>17 kcal mol^(-1).
文摘Signals from infrared detector are very weak in SO2 concentration measuring system.In order to improve the sensitivity of detection,combining with filter correlation technology and infrared absorption principle,the weak signal processing circuit is designed according to correlation detection technology.Under laboratory conditions,system performance of SO2 concentration is tested,and the experimental data are analyzed and processed.Then relationship of SO2 concentration and the measuring voltage is provided to prove that the design improves measuring sensitivity of the system.
基金supported by the National Natural Science Foundation of China (No.U1833203),the National Natural Science Foundation of China (No.62301036)the Aviation Science Foundation (No.2020Z019055001)China Postdoctoral Science Foundation Funded Project (No.2022M720446)。
文摘In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV).
文摘Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.
文摘This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden on the coast becomes a problem, both because erosion makes the cliffs unstable and because pollution increases, making the fragile dune ecosystem difficult to preserve. It is becoming necessary to increase the control of access to beaches, even if it is not a popular measure for internal and external tourism. The methodology described can also be used to monitor maritime borders. The use of images acquired in the infrared range guarantees active surveillance both day and night, the main objective being to mimic the infrared cameras already installed in some critical areas along the coastline. Using a series of infrared photographs taken at low angles with a modified camera and appropriate filter, a recent deep learning algorithm with the right training can simultaneously detect and count whole people at close range and people almost completely submerged in the water, including partially visible targets, achieving a performance with F1 score of 0.945, with 97% of targets correctly identified. This implementation is possible with ordinary laptop computers and could contribute to more frequent and more extensive coverage in beach/border surveillance, using infrared cameras at regular intervals. It can be partially automated to send alerts to the authorities and/or the nearest lifeguards, thus increasing monitoring without relying on human resources.
基金the support from the National Basic Research Program of China(No.613322)the Beijing Nova Program,China(No.Z200002121078)+1 种基金the National Natural Science Foundation of China(No.52202506)the Chinese Government Scholarship(CN)(No.201904980001)。
文摘As a key technology for space-based Earth observation and astronomical exploration,cooled mid-wavelength and long-wavelength Infrared(IR)detection is widely used in national defense,astronomy exploration,medical imaging,environmental monitoring,agricultural and other areas.The performances of IR detectors,including cut-off wavelength,detectivity,sensitivity and temperature resolution,plays a significant role in efficiently observing and tracking the low-temperature far-distance moving targets.Achieving optimal detection performance requires the IR detectors to operate at cryogenic temperatures.The future development of space-based applications relies heavily on the mid-wavelength and long-wavelength IR detection technologies,which should be enabled by the long-life cryogenic refrigeration and high-efficiency energy transportation system operating below 40 K,to support the Earth observation and astronomical detection.However,the efficiency degradation caused by the super low temperature brings tremendous challenges to the life time of cryogenic refrigeration and energy transportation systems.This paper evaluates the influence of cryogenic temperature on the infrared detector performances,reviews the features,development and space applications of cryogenic cooling technologies,as well as the cryogenic energy transportation approaches.Additionally,it analyzes the future development trends and challenges in supporting the space-based IR detection.
基金funded by National Natural Science Foundation of China,Fund Number 61703424.
文摘This paper proposes a real-time detection method to improve the Infrared small target detection CenterNet(ISTD-CenterNet)network for detecting small infrared targets in complex environments.The method eliminates the need for an anchor frame,addressing the issues of low accuracy and slow speed.HRNet is used as the framework for feature extraction,and an ECBAM attention module is added to each stage branch for intelligent identification of the positions of small targets and significant objects.A scale enhancement module is also added to obtain a high-level semantic representation and fine-resolution prediction map for the entire infrared image.Besides,an improved sensory field enhancement module is designed to leverage semantic information in low-resolution feature maps,and a convolutional attention mechanism module is used to increase network stability and convergence speed.Comparison experiments conducted on the infrared small target data set ESIRST.The experiments show that compared to the benchmark network CenterNet-HRNet,the proposed ISTD-CenterNet improves the recall by 22.85%and the detection accuracy by 13.36%.Compared to the state-of-the-art YOLOv5small,the ISTD-CenterNet recall is improved by 5.88%,the detection precision is improved by 2.33%,and the detection frame rate is 48.94 frames/sec,which realizes the accurate real-time detection of small infrared targets.
基金supported by The Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grants No.19JKB520031).
文摘Infrared target detection models are more required than ever before to be deployed on embedded platforms,which requires models with less memory consumption and better real-time performance while considering accuracy.To address the above challenges,we propose a modified You Only Look Once(YOLO)algorithm PF-YOLOv4-Tiny.The algorithm incorpo-rates spatial pyramidal pooling(SPP)and squeeze-and-excitation(SE)visual attention modules to enhance the target localization capability.The PANet-based-feature pyramid networks(P-FPN)are proposed to transfer semantic information and location information simultaneously to ameliorate detection accuracy.To lighten the network,the standard convolutions other than the backbone network are replaced with depthwise separable convolutions.In post-processing the images,the soft-non-maximum suppression(soft-NMS)algorithm is employed to subside the missed and false detection problems caused by the occlusion between targets.The accuracy of our model can finally reach 61.75%,while the total Params is only 9.3 M and GFLOPs is 11.At the same time,the inference speed reaches 87 FPS on NVIDIA GeForce GTX 1650 Ti,which can meet the requirements of the infrared target detection algorithm for the embedded deployments.
文摘Small infrared target detection has widespread applications in various fields including military,aviation,and medicine.However,detecting small infrared targets in complex backgrounds remains challenging.To detect small infrared targets,we propose a variable-structure U-shaped network referred as CAFUNet.A central differential convolution-based encoder,ASPP,an Attention Fusion module,and a decoder module are the critical components of the CAFUNet.The encoder module based on central difference convolution effectively extracts shallow detail information from infrared images,complemented by rich contextual information obtained from the deep features in the decoder module.However,the direct fusion of the shallow detail features with semantic features may lead to feature mismatch.To address this,we incorporate an Attention Fusion(AF)module to enhance the network performance further.We performed ablation studies on each module to evaluate its effectiveness.The results show that our proposed algorithm outperforms the state-of-the-art methods on publicly available datasets.
文摘Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.
文摘In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this paper.Firstly,the original infrared images are changed into a new infrared patch tensor mode through data reconstruction.Then,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of sparseness.Finally,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning algorithm.The test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm rate.It is a kind of infrared small and dim target detection method with good performance.
文摘This study aimed to propose road crack detection method based on infrared image fusion technology.By analyzing the characteristics of road crack images,this method uses a variety of infrared image fusion methods to process different types of images.The use of this method allows the detection of road cracks,which not only reduces the professional requirements for inspectors,but also improves the accuracy of road crack detection.Based on infrared image processing technology,on the basis of in-depth analysis of infrared image features,a road crack detection method is proposed,which can accurately identify the road crack location,direction,length,and other characteristic information.Experiments showed that this method has a good effect,and can meet the requirement of road crack detection.
基金supported by the Scientific and Innovative Action Plan of Shanghai(21N31900800)Shanghai Rising-Star Program(23QB1403500)+4 种基金the Shanghai Sailing Program(20YF1443000)Shanghai Science and Technology Commission,the Belt and Road Project(20310750500)Talent Project of SAAS(2023-2025)Runup Plan of SAAS(ZP22211)the SAAS Program for Excellent Research Team(2022(B-16))。
文摘Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.
基金This work was supported by the National Natural Science Foundation of China(Nos.12204499 and 62075225)Joint Key Projects of National Natural Science Foundation of China(No.U2032206)+1 种基金CAS Project for Young Scientists in Basic Research(No.YSBR-042)Open Project of State Key Laboratory of Surface Physics at Fudan University(No.KF2022_05).
文摘The infrared microspectroscopy beamline(BL06B) is a phase Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility(SSRF). The construction and optical alignment of BL06B were completed by the end of 2020. By 2021, it became accessible to users. The synchrotron radiation infrared(SRIR) source included edge radiation(ER) and bending magnet radiation(BMR). The extracted angles in the horizontal and vertical directions were 40 and 20 mrad, respectively. The photon flux, spectral resolution, and focused spot size were measured at the BL06B endstation, and the experimental results were consistent with theoretical calculations. SRIR light has a small divergence angle, high brightness, and a wide wavelength range. As a source of IR microscopy, it can easily focus on a diffraction-limited spatial resolution with a high signal-to-noise ratio(SNR). The BL06B endstation can be applied in a wide range of research fields, including materials, chemistry, biology, geophysics, and pharmacology.
文摘“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”
基金supported by the National Natural Science Foundation of China(Grant No.61975028)the Natural Science Foundation of Heilongjiang Province,China(Grant No.LH2022E004)the Postdoctoral Foundation of Heilongjiang Province,China(Grant No.LBH-Z22057).
文摘Accurate classification of rice variety is essential to ensure the brand value of high-quality rice products.Considering the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were selected.To enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).
基金supported by the National Natural Science Foundation of China(Grant Nos.12375244,12135009,and 12275356)the Hunan Provincial Innovation Foun-dation for Postgraduate(Grant Nos.CX20210062 and CX20230006).
文摘Relativistic femtosecond mid-infrared pulses can be generated efficiently by laser interaction with near-criticaldensity plasmas.It is found theoretically and numerically that the radiation pressure of a circularly polarized laser pulse first compresses the plasma electrons to form a dense flying mirror with a relativistic high speed.The pulse reflected by the mirror is red-shifted to the mid-infrared range.Full three-dimensional simulations demonstrate that the central wavelength of the mid-infrared pulse is tunable from 3µm to 14µm,and the laser energy conversion efficiency can reach as high as 13%.With a 0.5–10 PW incident laser pulse,the generated mid-infrared pulse reaches a peak power of 10–180 TW,which is interesting for various applications in ultrafast and high-field sciences.
