Many countries have set up ecological coastal preserves for sustainable oceans and ecological conservation and prohibiting people from angling along the shoreline. Although there are regular patrols by law enforcement officers, there are still many anglers who do not comply with the regulations, and intrude into the ecological coastal preserve. This requires a lot of human resources and time for law enforcement officers. Therefore, we developed a fishing detection system by collecting images of anglers’ fishing behaviors. We used a deep learning model with object detection and posture recognition. When anglers engaged in fishing behaviors, the system immediately transmitted the anglers’ geographic locations to the back-end database and notified the law enforcement officers. The results showed that the system’s accuracy rate in determining angling postures was as high as 90%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fishing Posture Detection Model Based on Convolutional Neural Network


    Contributors:


    Publication date :

    2023-12-01


    Size :

    858157 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Lateral distance detection model based on convolutional neural network

    Zhang, Xiang / Yang, Wei / Tang, Xiaolin et al. | Wiley | 2019

    Free access

    Lateral distance detection model based on convolutional neural network

    Zhang, Xiang / Yang, Wei / Tang, Xiaolin et al. | IET | 2018

    Free access

    Underwater posture adjusting device for fishing frame

    LIU YU / TANG JIWEI / WANG YU et al. | European Patent Office | 2022

    Free access


    Convolutional Neural Network GNSS-R Sea Ice Detection Based on AlexNet Model

    Zhihao, Jiang / Yuan, Hu / Xintai, Yuan et al. | Springer Verlag | 2022