Uncertainty Exploration: Toward Explainable SAR Target Detection
Author:
Affiliation:
1. BRain and Artificial INtelligence Laboratory (BRAIN Lab), School of Automation, Northwestern Polytechnical University, Xi’an, China
2. Beijing Institute of Mechanical and Electrical Engineering, Beijing, China
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Fundamental Research Funds for the Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10050159.pdf?arnumber=10050159
Reference43 articles.
1. Deep SAR-Net: Learning objects from signals
2. A comprehensive guide to Bayesian convolutional neural network with variational inference;shridhar;arXiv 1901 02731,2019
3. HDEC-TFA: An Unsupervised Learning Approach for Discovering Physical Scattering Properties of Single-Polarized SAR Image
4. Glassboxing Deep Learning to Enhance Aircraft Detection from SAR Imagery
5. What uncertainties do we need in Bayesian deep learning for computer vision?;kendall;arXiv 1703 04977,2017
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