Hyperspectral image denoising via self-modulated cross-attention deformable convolutional neural network-Reference-Cited by-同舟云学术

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Hyperspectral image denoising via self-modulated cross-attention deformable convolutional neural network

Published:2024-07-12 Issue:04 Volume:33 Page:
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:
Short-container-title:J. Electron. Imag.

Author:

Wang Ying¹,Qiu Jie²,Zhao Yanxiang³

Affiliation:

1. Henan University, Institute of Intelligence Networks System, School of Software, Kaifeng, China

2. Henan University, School of Software, Intelligent Data Processing Engineering Research Centre of Henan Province, Kaifeng, China

3. Henan University, School of Software, Kaifeng, China

Publisher

SPIE-Intl Soc Optical Eng

Reference54 articles.

1. Total Utility Metric Based Dictionary Pruning for Sparse Hyperspectral Unmixing

2. Deep spectral convolution network for hyperspectral image unmixing with spectral library

3. Ensemble and random collaborative representation-based anomaly detector for hyperspectral imagery

4. Hyperspectral image analysis. A tutorial

5. Quality estimation of nuts using deep learning classification of hyperspectral imagery

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