Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Laser & Optoelectronics Progress, Volume. 57, Issue 14, 141021(2020)

Low-Light Image Enhancement Based on Multi-Branch All Convolutional Neural Network

Ruoyou Wu, Dexing Wang*, Hongchun Yuan**, Peng Gong, Guanqi Chen, and Dan Wang
Author Affiliations
  • School of Information, Shanghai Ocean University, Shanghai 201306, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (0)
    References (38)
    Cited By (1)
    Tools
    Paper Information
    Topics
    Cited By

    Article index updated: Jun. 5, 2024

    The article is cited by 1 article(s) CLP online library. (Some content might be in Chinese.)
    Tools

    Get Citation

    Copy Citation Text

    Ruoyou Wu, Dexing Wang, Hongchun Yuan, Peng Gong, Guanqi Chen, Dan Wang. Low-Light Image Enhancement Based on Multi-Branch All Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141021

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Oct. 15, 2019

    Accepted: Dec. 17, 2019

    Published Online: Jul. 28, 2020

    The Author Email: Wang Dexing (dxwang@shou.edu.cn), Yuan Hongchun (hcyuan@shou.edu.cn)

    DOI:10.3788/LOP57.141021

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology