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Updated: Jul 23, 2025

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考虑图像信息和自我相似性:一个组成的否定网络.

Jiahong Zhang1, Yonggui Zhu2, Wenshu Yu3

  • 1The State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing 100024, China.

Sensors (Basel, Switzerland)
|July 14, 2023
PubMed
概括

本研究介绍了一种构成性否定网络 (CDN),通过解决残留学习中的局限性来改善图像否定. CDN有效地利用图像信息和自我相似性,以实现图像中的优异降噪.

关键词:
在美国,CNN是CNN.图像去色化 图像去色化剩余学习 剩余学习

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