Discriminating Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Review
Hyperspectral images (HSIs) contain subtle spectral details and rich spatial contextures of
land cover that benefit from developments in spectral imaging and space technology. The …
land cover that benefit from developments in spectral imaging and space technology. The …
Data and knowledge-driven deep multiview fusion network based on diffusion model for hyperspectral image classification
J Zhang, F Zhao, H Liu, J Yu - Expert Systems with Applications, 2024 - Elsevier
It is a crucial means for humans to perceive geomorphic features and landscape
architectures by classifying ground objects in hyperspectral images (HSIs). Currently, the …
architectures by classifying ground objects in hyperspectral images (HSIs). Currently, the …
Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation
Earth Observation (EO) data analysis has been significantly revolutionized by deep learning
(DL), with applications typically limited to grid-like data structures. Graph Neural Networks …
(DL), with applications typically limited to grid-like data structures. Graph Neural Networks …
Hyperspectral image classification using a large selective kernel network hybridized to-kenization transformer
Q Wan, Y He, W Gao, F Chen, W Chen - 2024 - preprints.opticaopen.org
One of the very popular deep learning-based techniques for classifying hyperspectral image
(HSI) is convolutional neural networks (CNNs). However, extensive spatial-spectral infor …
(HSI) is convolutional neural networks (CNNs). However, extensive spatial-spectral infor …
Exploring Cross-Dimensional Non-Local Self-Similarity for Hyperspectral and Multispectral Image Fusion
X Wang, Z Huang, J Zhu, X Wang, L Feng - Available at SSRN 4778143 - papers.ssrn.com
Hyperspectral image (HSI) and multispectral image (MSI) fusion is been regarded as an
economically feasible approach for obtaining high spatial resolution hyperspectral images …
economically feasible approach for obtaining high spatial resolution hyperspectral images …