CA-LOSS: A Cosine Affinity Loss for Imbalanced SAR Ship Classification-Reference-Cited by-同舟云学术

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CA-LOSS: A Cosine Affinity Loss for Imbalanced SAR Ship Classification

Published:2024-07-07 Issue: Volume: Page:9070-9074
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Xie Nishang¹,Xiong Mingkang²,Wei Feiming¹,Zhang Tao¹,Yang Zhen³,Yu Wenxian¹

Affiliation:

1. Shanghai Jiao Tong University,Shanghai Key Laboratory of Intelligent Sensing and Recognition,Shanghai,China,200240

2. Midea Corporate Research Center,Midea Group,Foshan,China,528311

3. Jiangxi Science and Technology Normal University,School of Communication and Electronics,Nanchang,China,330000

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640754.pdf?arnumber=10640754

Reference18 articles.

1. Ship Detection From PolSAR Imagery Using the Complete Polarimetric Covariance Difference Matrix

2. Imbalanced High-Resolution SAR Ship Recognition Method Based on a Lightweight CNN

3. Tackling SAR Imagery Ship Classification Imbalance via Deep Convolutional Generative Adversarial Network

4. C-SASO: A Clustering-Based Size-Adaptive Safer Oversampling Technique for Imbalanced SAR Ship Classification

5. Classification of Large-Scale High-Resolution SAR Images With Deep Transfer Learning

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