A lightweight model for echo trace detection in echograms based on improved YOLOv8
Abstract With the rise of underwater unmanned platforms like unmanned boats, ROVs, and AUVs, there’s an increasing need for underwater detection technologies. Researchers have merged scientific echosounders with these platforms for biometric applications. However, current detection models are too pa...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-82078-3 |
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| author | Jungang Ma Jianfeng Tong Minghua Xue Junfan Yao |
| author_facet | Jungang Ma Jianfeng Tong Minghua Xue Junfan Yao |
| author_sort | Jungang Ma |
| collection | DOAJ |
| description | Abstract With the rise of underwater unmanned platforms like unmanned boats, ROVs, and AUVs, there’s an increasing need for underwater detection technologies. Researchers have merged scientific echosounders with these platforms for biometric applications. However, current detection models are too parameter-heavy to embed in echosounders and struggle with noisy, irregular, and dense echograms. This paper introduces YOLOv8-SBE, a lightweight fish detection model based on YOLOv8, addressing these issues by enhancing feature extraction, information fusion, and small object recognition. YOLOv8-SBE adds the C2f_ScConv module to improve efficiency and reduce parameters, incorporates the BiFPN structure to enhance information transfer, and uses the EMA attention module for better small target recognition. It reduces computational complexity by 18.5%, decreases model parameters by 40%, and improves mAP0.5 to 79.5% and mAP0.5:0.95 to 58.2%, making it suitable for echosounders with limited resources. |
| format | Article |
| id | doaj-art-bb4449020d4141e5813a9ba9faafc98a |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-bb4449020d4141e5813a9ba9faafc98a2025-08-20T02:31:03ZengNature PortfolioScientific Reports2045-23222024-12-0114111710.1038/s41598-024-82078-3A lightweight model for echo trace detection in echograms based on improved YOLOv8Jungang Ma0Jianfeng Tong1Minghua Xue2Junfan Yao3College of Marine Living Resource Sciences and Management, Shanghai Ocean UniversityCollege of Marine Living Resource Sciences and Management, Shanghai Ocean UniversityCollege of Marine Living Resource Sciences and Management, Shanghai Ocean UniversityCollege of Marine Living Resource Sciences and Management, Shanghai Ocean UniversityAbstract With the rise of underwater unmanned platforms like unmanned boats, ROVs, and AUVs, there’s an increasing need for underwater detection technologies. Researchers have merged scientific echosounders with these platforms for biometric applications. However, current detection models are too parameter-heavy to embed in echosounders and struggle with noisy, irregular, and dense echograms. This paper introduces YOLOv8-SBE, a lightweight fish detection model based on YOLOv8, addressing these issues by enhancing feature extraction, information fusion, and small object recognition. YOLOv8-SBE adds the C2f_ScConv module to improve efficiency and reduce parameters, incorporates the BiFPN structure to enhance information transfer, and uses the EMA attention module for better small target recognition. It reduces computational complexity by 18.5%, decreases model parameters by 40%, and improves mAP0.5 to 79.5% and mAP0.5:0.95 to 58.2%, making it suitable for echosounders with limited resources.https://doi.org/10.1038/s41598-024-82078-3 |
| spellingShingle | Jungang Ma Jianfeng Tong Minghua Xue Junfan Yao A lightweight model for echo trace detection in echograms based on improved YOLOv8 Scientific Reports |
| title | A lightweight model for echo trace detection in echograms based on improved YOLOv8 |
| title_full | A lightweight model for echo trace detection in echograms based on improved YOLOv8 |
| title_fullStr | A lightweight model for echo trace detection in echograms based on improved YOLOv8 |
| title_full_unstemmed | A lightweight model for echo trace detection in echograms based on improved YOLOv8 |
| title_short | A lightweight model for echo trace detection in echograms based on improved YOLOv8 |
| title_sort | lightweight model for echo trace detection in echograms based on improved yolov8 |
| url | https://doi.org/10.1038/s41598-024-82078-3 |
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