A Global Model Approach to Robust Few-Shot SAR Automatic Target Recognition
Author:
Affiliation:
1. Air Force Research Laboratory Information Directorate (AFRL/RI), High-Performance Systems Branch Rome, Rome, NY, USA
Funder
Air Force Research Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/10034981/10092792.pdf?arnumber=10092792
Reference23 articles.
1. FUSAR-Ship: building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition
2. HRSID: A high-resolution SAR images dataset for ship detection and instance segmentation;wei;IEEE Access,2020
3. A baseline for detecting misclassified and out-of-distribution examples in neural networks;hendrycks;Proc Int Conf Learn Represent,2017
4. LS-SSDD-v1.0: A Deep Learning Dataset Dedicated to Small Ship Detection from Large-Scale Sentinel-1 SAR Images
5. SAR Ship Detection Dataset (SSDD): Official Release and Comprehensive Data Analysis
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