Hyperspectral Target Detection Based on Weighted Cauchy Distance Graph and Local Adaptive Collaborative Representation
Author:
Affiliation:
1. Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technology, Beijing, China
2. College of Information and Communication Engineering, Harbin Engineering University, Harbin, China
Funder
National Natural Science Foundation of China
Beijing Natural Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09762288.pdf?arnumber=9762288
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Sliding Dual-Window-Inspired Reconstruction Network for Hyperspectral Anomaly Detection;IEEE Transactions on Geoscience and Remote Sensing;2024
2. Hyperspectral anomaly detection based on variational background inference and generative adversarial network;Pattern Recognition;2023-11
3. An Attention-Based Multiscale Spectral–Spatial Network for Hyperspectral Target Detection;IEEE Geoscience and Remote Sensing Letters;2023
4. Bayesian Target Detection Algorithms for Solid Subpixel Targets in Hyperspectral Images;IEEE Transactions on Geoscience and Remote Sensing;2023
5. A Multidepth and Multibranch Network for Hyperspectral Target Detection Based on Band Selection;IEEE Transactions on Geoscience and Remote Sensing;2023
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