C-SASO: A Clustering-Based Size-Adaptive Safer Oversampling Technique for Imbalanced SAR Ship Classification-Reference-Cited by-同舟云学术

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

Author:

Li Yongxu¹^ORCID,Lai Xudong¹,Wang Mingwei²,Zhang Xi³

Affiliation:

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

2. School of Computer Science, Hubei University of Technology, Wuhan, China

3. Laboratory of Marine Physics and Remote Sensing, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference49 articles.

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2. CA-LOSS: A Cosine Affinity Loss for Imbalanced SAR Ship Classification;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07