Tsu-Yang Wu1,2, Haonan Li2, Saru Kumari3, Chien-Ming Chen1,*
CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 19-46, 2024, DOI:10.32604/cmc.2024.048347
Abstract Hyperspectral image classification stands as a pivotal task within the field of remote sensing, yet achieving high-precision 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 algorithm can adjust the weights according to the change in the number of iterations to improve the performance of the algorithm. Gaussian mutation helps the algorithm avoid… More >
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