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A Novel Classification Framework for Hyperspectral Image Data by Improved Multilayer Perceptron Combined with Residual Network
2022
Symmetry
Convolutional neural networks (CNNs) have attracted extensive attention in the field of modern remote sensing image processing and show outstanding performance in hyperspectral image (HSI) classification. Nevertheless, some hyperspectral images have fixed position priors and parameter sharing between different positions, so the common convolution layer may ignore some important fine and useful information and cannot guarantee to effectively capture the optimal image features. This paper
doi:10.3390/sym14030611
fatcat:s6dhg4uperhzzkz2cuuz4fgtvq