Cross-Level Semantic Segmentation Guided Feature Space Decoupling And Augmentation for Fine-Grained Ship Detection-Reference-Cited by-同舟云学术

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Cross-Level Semantic Segmentation Guided Feature Space Decoupling And Augmentation for Fine-Grained Ship Detection

Published:2022-08-29 Issue: Volume: Page:
ISSN:
Container-title:2022 30th European Signal Processing Conference (EUSIPCO)
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Author:

Zhang Zhengning¹,Zhang Lin²,Wang Yue³,Feng Pengming⁴,Liu Shaobo⁵,Wang Jian⁵

Affiliation:

1. Tsinghua University and Space Star Technology Co. Ltd.,Beijing,China

2. Tsinghua Shenzhen International, Graduate School,Shenzhen,China

3. Tsinghua University,Department of Electronic Engineering,Beijing,China

4. Integrated Information Technology,State Key Laboratory of Space-Ground,Beijing,China

5. Space Star Technology Co. Ltd.,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9908519/9909515/09909586.pdf?arnumber=9909586

Reference10 articles.

1. Deep Representation Learning on Long-Tailed Data: A Learnable Embedding Augmentation Perspective

2. Deep long-tailed learning: A survey;zhang;ArXiv Preprint,2021

3. Efficient Cipher-Only Attack of a Stream Cipher in RDHEI Based on Pixel Smoothness Estimation

4. ShipRSImageNet: A Large-Scale Fine-Grained Dataset for Ship Detection in High-Resolution Optical Remote Sensing Images

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A data augmentation method for fine-grained ship detection in remote sensing images;Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023);2024-01-23

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