Deep Network-Enabled Haze Visibility Enhancement for Visual IoT-Driven Intelligent Transportation Systems-Reference-Cited by-同舟云学术

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Deep Network-Enabled Haze Visibility Enhancement for Visual IoT-Driven Intelligent Transportation Systems

Published:2023-02 Issue:2 Volume:19 Page:1581-1591
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Liu Ryan Wen¹^ORCID,Guo Yu¹^ORCID,Lu Yuxu¹^ORCID,Chui Kwok Tai²^ORCID,Gupta Brij B.³^ORCID

Affiliation:

1. School of Navigation, Wuhan University of Technology, Wuhan, China

2. School of Science and Technology, Hong Kong Metropolitan University, Kowloon, Hong Kong

3. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/9989328/09764372.pdf?arnumber=9764372

Reference40 articles.

1. A Survey on Multi-Task Learning

2. An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system

3. MegaDepth: Learning Single-View Depth Prediction from Internet Photos

4. Single Image Dehazing Using Haze-Lines

5. The Pascal Visual Object Classes (VOC) Challenge

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