Binocular Vision of Fish Swarm Detection in Real-time Based on Deep Learning

被引:0
|
作者
Xu, Lixue [1 ]
Wei, Yanhui [1 ]
Wang, Xiubo [1 ]
Wang, Anqi [1 ]
Guan, Lianwu [1 ]
机构
[1] Harbin Engn Univ, Coll Automat, Harbin 15001, Heilongjiang, Peoples R China
关键词
Fish swarm detection; Deep Learning detection; Binocular vision; Regression network; Improved SURF; Radar map;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
in the field of ocean development, fish swarm detection has significance for AUV's autonomous navigation and fishing industry. Aim to present fish swarm detections are common based on 21) which lack of spatial information, has low accuracy and bad real-time performance, so we proposed systematic fish swarm detection and position method. We used deep learning target detection system to detect fish and used binocular vision position system to position, then fused every fish's 3D information in camera vision to displayed fish swarm spatial information through radar map. Finally, the contrast experiment and is carried out to verify the effectiveness of the proposed method.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Real-time detection of panoramic multitargets based on machine vision and deep learning
    Shen, Keyong
    Yang, Yang
    Zhang, Xiaoyu
    JOURNAL OF ELECTRONIC IMAGING, 2022, 31 (05)
  • [2] Real-time detection of deep-sea hydrothermal plume based on machine vision and deep learning
    Wang, Xun
    Cao, Yanpeng
    Wu, Shijun
    Yang, Canjun
    FRONTIERS IN MARINE SCIENCE, 2023, 10
  • [3] Real-Time Lane Detection Based on Deep Learning
    Sun-Woo Baek
    Myeong-Jun Kim
    Upendra Suddamalla
    Anthony Wong
    Bang-Hyon Lee
    Jung-Ha Kim
    Journal of Electrical Engineering & Technology, 2022, 17 : 655 - 664
  • [4] Real-Time Lane Detection Based on Deep Learning
    Baek, Sun-Woo
    Kim, Myeong-Jun
    Suddamalla, Upendra
    Wong, Anthony
    Lee, Bang-Hyon
    Kim, Jung-Ha
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2022, 17 (01) : 655 - 664
  • [5] Vision-Based Deep Learning Approach for Real-Time Detection of Weeds in Organic Farming
    Czymmek, Vitali
    Harders, Leif O.
    Knoll, Florian J.
    Hussmann, Stephan
    2019 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC), 2019, : 585 - 589
  • [6] Real-Time Binocular Stereo Vision System Based on FPGA
    Ma, Jiawei
    Yin, Wei
    Zuo, Chao
    Feng, Shijie
    Chen, Qian
    SIXTH INTERNATIONAL CONFERENCE ON OPTICAL AND PHOTONIC ENGINEERING (ICOPEN 2018), 2018, 10827
  • [7] A Real-time Ranging Method Based on Parallel Binocular Vision
    Xu, Huantai
    Liu, Xia
    Zhu, Chengfei
    Li, Shuxiao
    Chang, Hongxing
    2017 10TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL. 1, 2017, : 183 - 187
  • [8] Real-time detection of distracted driving based on deep learning
    Duy Tran
    Ha Manh Do
    Sheng, Weihua
    Bai, He
    Chowdhary, Girish
    IET INTELLIGENT TRANSPORT SYSTEMS, 2018, 12 (10) : 1210 - 1219
  • [9] Deep learning based anomaly detection in real-time video
    Elmetwally A.
    Eldeeb R.
    Elmougy S.
    Multimedia Tools and Applications, 2025, 84 (11) : 9555 - 9571
  • [10] Real-Time, Deep Learning Based Wrong Direction Detection
    Usmankhujaev, Saidasul
    Baydadaev, Shokhrukh
    Woo, Kwon Jang
    APPLIED SCIENCES-BASEL, 2020, 10 (07):