电子科技大学学报2025，Vol.54Issue(4)：554-565,12.DOI:10.12178/1001-0548.2024139
基于双模型决策级融合的鱼道分布外目标检测方法
Out-of-distribution fish detection in fishways based on decision-level fusion of two models
摘要
Abstract
To address the issues of missed detection and false alarms resulting from ambiguous fish features and insufficient prior information in the dataset for fish detection in fishways,this paper proposes an object detection algorithm founded on decision fusion between coarse-grained and fine-grained YOLO models.The method enhances the coarse-grained YOLO model by embedding a coordinate attention module into the backbone layers and an adaptive spatial feature fusion module into the feature aggregation part to fuse features from different scale layers,thereby improving the model's detection capability for arbitrary fish species.The detection outcomes from the refined coarse-grained YOLO model and fine-grained YOLO model are filtered by confidence scores to identify boxes that need fusion.These boxes are then weighted fused based on their confidence values.This allows the proposed approach to attain a lower miss rate and false alarm rate for out-of-distribution detection on unknown and blurry fish.Evaluated on real-world fishway fish datasets,The proposed method achieves 98.59%accuracy and 94.19%recall for unknown fish,which are 9.25%and 11.21%higher than the confidence-based out-of-distribution detection method,and 6.42%and 3.69%higher than the energy-based out-of-distribution detection method,respectively.The recognition accuracy of fuzzy targets reaches 95.45%and the recall rate reaches 91.8%,which is 16.63%and 18.58%higher than the confidence-based out-of-distribution detection method,and 11.27%and 1.74%higher than the energy-based out-of-distribution detection method,respectively.The research findings have valuable implications for fish detection in fishways.关键词
鱼道/目标检测/YOLO/注意力机制/自适应特征融合/决策级融合/分布外检测Key words
fishways/object detection/YOLO/attention mechanism/adaptive feature fusion/decision fusion/out-of-distribution detection分类
信息技术与安全科学引用本文复制引用
牛睿智,刘志亮,周雪,梅燕..基于双模型决策级融合的鱼道分布外目标检测方法[J].电子科技大学学报,2025,54(4):554-565,12.基金项目
国家自然科学基金(62372082) （62372082）
中央高校基本科研业务费(ZYGX2024Z017) （ZYGX2024Z017）
深圳市自然科学基金(JCYJ20240813114206010) （JCYJ20240813114206010）
四川省科技计划(2024JDHJ0057) （2024JDHJ0057）
