Research Article
Fish recognition in underwater fuzzy environment based on deep learning
@INPROCEEDINGS{10.4108/eai.24-2-2023.2330667, author={Xiangyu Wu and Huimin Li and Junyao Hong}, title={Fish recognition in underwater fuzzy environment based on deep learning}, proceedings={Proceedings of the 2nd International Conference on Engineering Management and Information Science, EMIS 2023, February 24-26, 2023, Chengdu, China}, publisher={EAI}, proceedings_a={EMIS}, year={2023}, month={6}, keywords={yolov4; fish recognition; fuzzy environment}, doi={10.4108/eai.24-2-2023.2330667} }- Xiangyu Wu
Huimin Li
Junyao Hong
Year: 2023
Fish recognition in underwater fuzzy environment based on deep learning
EMIS
EAI
DOI: 10.4108/eai.24-2-2023.2330667
Abstract
This study focuses on the development of an underwater fish recognition algorithm using the YOLOv4 deep learning framework. It begins by providing background information on underwater fish recognition, followed by an overview of object detection and recognition techniques. The YOLOv4 algorithm is then discussed in detail, including its network architecture, feature extraction module, loss function, and backpropagation process. The study evaluates the algorithm's performance through simulation results and comparisons with other algorithms. Additionally, limitations and challenges of the YOLOv4 algorithm for underwater recognition are identified, and potential future directions for enhancing its accuracy and robustness are discussed.
