Deep Self-Representation Learning Framework for Hyperspectral Anomaly Detection
Author:
Affiliation:
1. School of Aerospace Science and Technology, Xidian University, Xi’an, China
2. State Key Laboratory of Integrated Service Network, Xidian University, Xi’an, China
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10367905/10309883.pdf?arnumber=10309883
Reference74 articles.
1. Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
2. Incorporating the Completeness and Difficulty of Proposals Into Weakly Supervised Object Detection in Remote Sensing Images
3. Mining High-Quality Pseudoinstance Soft Labels for Weakly Supervised Object Detection in Remote Sensing Images
4. Remote sensing for agricultural applications: A meta-review
5. Hyperspectral Image Classification via Multiple-Feature-Based Adaptive Sparse Representation
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