Gated residual feature attention network for real-time Dehazing

Weichao Yi; Liquan Dong; Ming Liu; Yuejin Zhao; Mei Hui; Lingqin Kong

doi:10.1007/s10489-022-03157-4

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JOURNAL ARTICLE

Gated residual feature attention network for real-time Dehazing

Weichao Yi Liquan Dong Ming Liu Yuejin Zhao Mei Hui Lingqin Kong

Year: 2022 Journal: Applied Intelligence Vol: 52 (15)Pages: 17449-17464 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-03157-4

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Keywords:

Computer science Residual Artificial intelligence Feature (linguistics) Merge (version control) Block (permutation group theory) Pattern recognition (psychology) Feature extraction Computer vision Algorithm

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Image Enhancement Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Fire Detection and Safety Systems

Physical Sciences → Engineering → Safety, Risk, Reliability and Quality

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Gated residual feature attention network for real-time Dehazing

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