HFMNet: Hierarchical Feature Mining Network for Low-Light Image Enhancement-Reference-Cited by-同舟云学术

HFMNet: Hierarchical Feature Mining Network for Low-Light Image Enhancement

Author:

Xu Kai¹^ORCID,Chen Huaian¹^ORCID,Tan Xiao¹^ORCID,Chen Yuxuan¹^ORCID,Jin Yi²^ORCID,Kan Yan³^ORCID,Zhu Changan²^ORCID

Affiliation:

1. School of Engineering Science, University of Science and Technology of China, Hefei, Anhui, China

2. School of Engineering Science and the School of Data Science, University of Science and Technology of China, Hefei, Anhui, China

3. Innovation Laboratory of WuHu State-owned Factory of Machining, University of Science and Technology of China, Hefei Anhui, China

Funder

National Natural Science Foundation of China

Special Fund for Key Program of Science and Technology of Anhui Province

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference59 articles.

3. Image super-resolution using very deep residual channel attention networks;zhang;Proc Eur Conf Comput Vis,2018

4. Deep retinex decomposition for low-light enhancement;wei;arXiv 1808 04560,2018

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