1 citations · 1 across the 6 of their papers we have counts for
6 papers
Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive Gating
Guandong Li, Mengxia Ye
Deep neural networks face several challenges in hyperspectral image classification, including high-dimensional data, sparse distribution of ground objects, and spectral redundancy,…
Expert Kernel Generation Network Driven by Contextual Mapping for Hyperspectral Image Classification
Guandong Li, Mengxia Ye
Deep neural networks face several challenges in hyperspectral image classification, including high-dimensional data, sparse distribution of ground objects, and spectral redundancy,…
3D Wavelet Convolutions with Extended Receptive Fields for Hyperspectral Image Classification
Guandong Li, Mengxia Ye
Deep neural networks face numerous challenges in hyperspectral image classification, including high-dimensional data, sparse ground object distributions, and spectral redundancy, w…
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification
Guandong Li, Mengxia Ye
Deep neural networks face several challenges in hyperspectral image classification, including complex and sparse ground object distributions, small clustered structures, and elonga…
Efficient Dynamic Attention 3D Convolution for Hyperspectral Image Classification
Guandong Li, Mengxia Ye
Deep neural networks face several challenges in hyperspectral image classification, including insufficient utilization of joint spatial-spectral information, gradient vanishing wit…
Spatial-Spectral Hyperspectral Classification based on Learnable 3D Group Convolution
Guandong Li, Mengxia Ye
Deep neural networks have faced many problems in hyperspectral image classification, including the ineffective utilization of spectral-spatial joint information and the problems of…