Underwater Attentional Generative Adversarial Networks for Image Enhancement

Article Properties
  • DOI (url)
    10.1109/thms.2023.3261341
  • Publication Date
    2023/06/01
  • Journal
    IEEE Transactions on Human-Machine Systems
  • Indian UGC (journal)
  • Refrences
    50
  • Ning Wang School of Marine Engineering, Dalian Maritime University, Dalian, China ORCID (unauthenticated)
  • Tingkai Chen School of Marine Electrical Engineering, Dalian Maritime University, Dalian, China
  • Xiangjun Kong School of Marine Electrical Engineering, Dalian Maritime University, Dalian, China
  • Yanzheng Chen School of Marine Engineering, Dalian Maritime University, Dalian, China
  • Rongfeng Wang School of Marine Electrical Engineering, Dalian Maritime University, Dalian, China
  • Yongjun Gong School of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, China
  • Shiji Song Department of Automation, Tsinghua University, Beijing, China ORCID (unauthenticated)
Cite
Wang, Ning, et al. “Underwater Attentional Generative Adversarial Networks for Image Enhancement”. IEEE Transactions on Human-Machine Systems, vol. 53, no. 3, 2023, pp. 490-0, https://doi.org/10.1109/thms.2023.3261341.
Wang, N., Chen, T., Kong, X., Chen, Y., Wang, R., Gong, Y., & Song, S. (2023). Underwater Attentional Generative Adversarial Networks for Image Enhancement. IEEE Transactions on Human-Machine Systems, 53(3), 490-500. https://doi.org/10.1109/thms.2023.3261341
Wang N, Chen T, Kong X, Chen Y, Wang R, Gong Y, et al. Underwater Attentional Generative Adversarial Networks for Image Enhancement. IEEE Transactions on Human-Machine Systems. 2023;53(3):490-50.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Engineering (General)
Civil engineering (General)
Technology
Mechanical engineering and machinery
Refrences
Title Journal Journal Categories Citations Publication Date
Auto color correction of underwater images utilizing depth information IEEE Geoscience and Remote Sensing Letters
  • Science: Geology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Geography. Anthropology. Recreation: Geography (General)
  • Technology: Photography
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Geology
 2022
CBAM: Convolutional block attention module 0
Diving into haze-lines: Color restoration of underwater images 0
Review on deep learning techniques for marine object recognition: Architectures and algorithms Control Engineering Practice
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 2021
U-Net: Convolutional networks for biomedical image segmentation 0