Simulated Data Feature Guided Evolution and Distillation for Incremental SAR ATR-Reference-Cited by-同舟云学术

Simulated Data Feature Guided Evolution and Distillation for Incremental SAR ATR

Published:2024 Issue: Volume:62 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xu Yanjie¹^ORCID,Sun Hao¹^ORCID,Zhao Yan¹,He Qishan¹,Zhang Siqian¹^ORCID,Kuang Gangyao¹,Chen Hui²^ORCID

Affiliation:

1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System and the College of Electronic Science and Technology, National University of Defense Technology, Changsha, China

2. State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10574846.pdf?arnumber=10574846

Reference82 articles.

1. Augmenting Simulations for SAR ATR Neural Network Training

2. A SAR dataset for ATR Development: the Synthetic and Measured Paired Labeled Experiment (SAMPLE)

3. Fast 3D-ISAR Image Simulation of Targets at Arbitrary Aspect Angles Through Nonuniform Fast Fourier Transform (NUFFT)

4. Few-Shot Class-Incremental SAR Target Recognition Based on Hierarchical Embedding and Incremental Evolutionary Network

5. Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer

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