A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers and Mamba Models
Hyperspectral Image Classification (HSC) presents significant challenges owing to the high
dimensionality and intricate nature of Hyperspectral (HS) data. While traditional Machine …
dimensionality and intricate nature of Hyperspectral (HS) data. While traditional Machine …
Fusing transformers in a tuning fork structure for hyperspectral image classification across disjoint samples
The 3-D swin transformer (3DST) and spatial–spectral transformer (SST) each excel in
capturing distinct aspects of image information: the 3DST with hierarchical attention and …
capturing distinct aspects of image information: the 3DST with hierarchical attention and …
Dual attention transformer network for hyperspectral image classification
Z Shu, Y Wang, Z Yu - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Hyperspectral image classification (HSIC) has been a significant topic in the field of remote
sensing in the past few years. Convolutional neural networks have shown promising …
sensing in the past few years. Convolutional neural networks have shown promising …
Spectral-enhanced sparse transformer network for hyperspectral super-resolution reconstruction
Y Yang, Y Wang, H Wang, L Zhang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Hyperspectral image (HSI) has garnered increasing attention due to its capacity for
capturing extensive spectral information. However, the acquisition of high spatial resolution …
capturing extensive spectral information. However, the acquisition of high spatial resolution …
A CNN-transformer embedded unfolding network for hyperspectral image super-resolution
Hyperspectral images (HSIs) with rich spectral information have been widely used in surface
classification, object detection, and other real application problems. However, due to the …
classification, object detection, and other real application problems. However, due to the …
Cross-scope spatial-spectral information aggregation for hyperspectral image super-resolution
S Chen, L Zhang, L Zhang - IEEE Transactions on Image …, 2024 - ieeexplore.ieee.org
Hyperspectral image super-resolution has attained widespread prominence to enhance the
spatial resolution of hyperspectral images. However, convolution-based methods have …
spatial resolution of hyperspectral images. However, convolution-based methods have …
AS3ITransUNet: Spatial-Spectral Interactive Transformer U-Net with Alternating Sampling for Hyperspectral Image Super-Resolution
Q Xu, S Liu, J Wang, B Jiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Single hyperspectral image (HSI) super-resolution (SR) is an important topic in the remote-
sensing field. However, existing HSI SR methods mainly use the feed-forward upsampling …
sensing field. However, existing HSI SR methods mainly use the feed-forward upsampling …
Wavelet Tree Transformer: Multi-Head Attention with Frequency Selective Representation and Interaction for Remote Sensing Object Detection
J Pan, C He, W Huang, J Cao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vision Transformer has achieved remarkable success in image recognition tasks owing to its
global modeling ability. However, the quadratic computational complexity becomes a …
global modeling ability. However, the quadratic computational complexity becomes a …
An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea
F Zhu, J Wang, Y Zhang, J Shi, M He, Z Zhao - Food Control, 2025 - Elsevier
Fermentation is a key process in forming the flavor quality of black tea. Evaluating the
degree of fermentation during black tea processing is difficult. This paper proposes an …
degree of fermentation during black tea processing is difficult. This paper proposes an …
Cross-spatial pixel integration and cross-stage feature fusion-based transformer network for remote sensing image super-resolution
Remote sensing image super-resolution (RSISR) plays a vital role in enhancing spatial
details and improving the quality of satellite imagery. Recently, Transformer-based models …
details and improving the quality of satellite imagery. Recently, Transformer-based models …