A mixture of experts image enhancement scheme for CCTV images

被引：0
|
作者：
Singh, M [1 ]
Singh, S [1 ]
Porter, M [1 ]
机构：
[1] Univ Exeter, Dept Comp Sci, ATR Lab, Exeter EX4 4QF, Devon, England
来源：
INTELLIGENT DAA ENGINEERING AND AUTOMATED LEARNING IDEAL 2004, PROCEEDINGS | 2004年 / 3177卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The main aim of this paper is to present a mixture of experts framework for the selection of an optimal image enhancement. This scheme selects the best image enhancement algorithm from a bank of algorithms on a per image basis. The results show that this scheme considerably improves the quality of test images collected from CCTV.
引用
收藏
页码：185 / 190
页数：6
相关论文
共 50 条
  • [21] DeepME: Deep Mixture Experts for Large-scale Image Classification
    He, Ming
    Lv, Guangyi
    He, Weidong
    Fan, Jianping
    Zeng, Guihua
    PROCEEDINGS OF THE THIRTIETH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2021, 2021, : 722 - 728
  • [22] Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts
    Mustafa, Basil
    Riquelme, Carlos
    Puigcerver, Joan
    Jenatton, Rodolphe
    Houlsby, Neil
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [23] A DNA Computation-Based Image Encryption Scheme for Cloud CCTV Systems
    Wu, Tsu-Yang
    Fan, Xiaoning
    Wang, King-Hang
    Lai, Chin-Feng
    Xiong, Naixue
    Wu, Jimmy Ming-Tai
    IEEE ACCESS, 2019, 7 : 181434 - 181443
  • [24] Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
    Ou, Yanglan
    Yuan, Ye
    Huang, Xiaolei
    Wong, Stephen T. C.
    Volpi, John
    Wang, James Z.
    Wong, Kelvin
    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT V, 2022, 13435 : 475 - 484
  • [25] A Mixture of Experts Approach to Multi-strategy Image Quality Assessment
    Peng, Peng
    Li, Ze-Nian
    IMAGE ANALYSIS AND RECOGNITION, PT I, 2012, 7324 : 123 - 130
  • [26] MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation
    Park, David Keetae
    Yoo, Seungjoo
    Bahng, Hyojin
    Choo, Jaegul
    Park, Noseong
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 878 - 884
  • [27] A secure visual secret sharing (VSS) scheme with CNN-based image enhancement for underwater images
    Mhala, Nikhil C.
    Pais, Alwyn R.
    VISUAL COMPUTER, 2021, 37 (08): : 2097 - 2111
  • [28] A secure visual secret sharing (VSS) scheme with CNN-based image enhancement for underwater images
    Nikhil C. Mhala
    Alwyn R. Pais
    The Visual Computer, 2021, 37 : 2097 - 2111
  • [29] Speech enhancement using deep mixture of experts based on hard expectation maximization
    Karjol, Pavan
    Ghosh, Prasanta Kumar
    19TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2018), VOLS 1-6: SPEECH RESEARCH FOR EMERGING MARKETS IN MULTILINGUAL SOCIETIES, 2018, : 3254 - 3258
  • [30] SPEECH ENHANCEMENT WITH MIXTURE OF DEEP EXPERTS WITH CLEAN CLUSTERING PRE-TRAINING
    Chazan, Shlomo E.
    Goldberger, Jacob
    Gannot, Sharon
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 716 - 720
12345