Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convol...Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.展开更多
随着全球环保运动的风行，环保理念日渐深入人心。许多大牌都以环保为主题设计推出了便宜又实用的包包。近日，Marc Jacobs推出了一款环保拎包，外型简洁，清新的白色配以黑色的“MARC JACOBS”与”NEW YORK SINCE 1984”标记．令消费...随着全球环保运动的风行，环保理念日渐深入人心。许多大牌都以环保为主题设计推出了便宜又实用的包包。近日，Marc Jacobs推出了一款环保拎包，外型简洁，清新的白色配以黑色的“MARC JACOBS”与”NEW YORK SINCE 1984”标记．令消费者真正感受到环保带来的健康、时尚的生活方式。展开更多
近日，来自美国的MARC BY MARC JACOBS于铜锣湾开设香港首家旗舰专门店。Marc Jacobs的一线品牌MARC JACOBS的成熟型设计风格稳重大气，颇受女士们欢迎，但是说到精致细巧的细节设计，则还是其副线品牌MAPC BY MARC，JACOBS更胜一筹。...近日，来自美国的MARC BY MARC JACOBS于铜锣湾开设香港首家旗舰专门店。Marc Jacobs的一线品牌MARC JACOBS的成熟型设计风格稳重大气，颇受女士们欢迎，但是说到精致细巧的细节设计，则还是其副线品牌MAPC BY MARC，JACOBS更胜一筹。这也印证了如今副线品牌往往比一线品牌更受欢迎的规律。展开更多
基金Natural Science Foundation of Shandong Province,China(Grant No.ZR202111230202).
文摘Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.
文摘随着全球环保运动的风行，环保理念日渐深入人心。许多大牌都以环保为主题设计推出了便宜又实用的包包。近日，Marc Jacobs推出了一款环保拎包，外型简洁，清新的白色配以黑色的“MARC JACOBS”与”NEW YORK SINCE 1984”标记．令消费者真正感受到环保带来的健康、时尚的生活方式。
文摘近日，来自美国的MARC BY MARC JACOBS于铜锣湾开设香港首家旗舰专门店。Marc Jacobs的一线品牌MARC JACOBS的成熟型设计风格稳重大气，颇受女士们欢迎，但是说到精致细巧的细节设计，则还是其副线品牌MAPC BY MARC，JACOBS更胜一筹。这也印证了如今副线品牌往往比一线品牌更受欢迎的规律。
