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Hyperspectral image super-resolution meets deep learning: A survey and perspective
Hyperspectral image super-resolution, which refers to reconstructing the high-resolution
hyperspectral image from the input low-resolution observation, aims to improve the spatial …
hyperspectral image from the input low-resolution observation, aims to improve the spatial …
Essaformer: Efficient transformer for hyperspectral image super-resolution
Single hyperspectral image super-resolution (single-HSI-SR) aims to restore a high-
resolution hyperspectral image from a low-resolution observation. However, the prevailing …
resolution hyperspectral image from a low-resolution observation. However, the prevailing …
Interactformer: Interactive transformer and CNN for hyperspectral image super-resolution
Due to rich spectral information, hyperspectral images (HSIs) have been widely used in
various fields. However, limited by imaging systems, the low spatial resolution of HSIs has …
various fields. However, limited by imaging systems, the low spatial resolution of HSIs has …
Hyperspectral image super-resolution with ConvLSTM skip-connections
Y Xu, J Hou, X Zhu, C Wang, H Shi… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Hyperspectral image super-resolution has been extensively studied, and significant
development has been made based on deep convolutional neural networks (CNNs) …
development has been made based on deep convolutional neural networks (CNNs) …
Feature preservation and shape cues assist infrared small target detection
Infrared small target detection (ISTD) aims to segment small target pixels from infrared
images and has extensive applications in many fields. Despite multiple progress, challenges …
images and has extensive applications in many fields. Despite multiple progress, challenges …
[HTML][HTML] DCFF-Net: Deep Context Feature Fusion Network for High-Precision Classification of Hyperspectral Image
Z Chen, Y Chen, Y Wang, X Wang, X Wang, Z **. This process is typically managed using multilayer …