上海海洋大学信息学院
纸质出版:2025
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王飞飞, 秦玉芳, 冯国富, 等. 用于复杂水下环境下的轻量级目标检测算法[J]. 传感器与微系统, 2025,(4):137-142+147.
王飞飞, 秦玉芳, 冯国富, 等. 用于复杂水下环境下的轻量级目标检测算法[J]. 传感器与微系统, 2025,(4):137-142+147. DOI: 10.13873/J.1000-9787(2025)04-0137-06.
在利用水下机器人进行生物捕捞与识别时,色偏、雾效应与光干扰等复杂水下环境的干扰会导致模型存在漏检和误检现象,同时,由于带宽受限,水下设备计算资源也受限制。为解决上述问题,提出了一种高检测精度的轻量级改进的YOLOv7-tiny模型。使用SiLU激活函数和EIOU损失函数提高模型收敛速度;使用双重注意力叠加的GAM注意力机制和三重注意力叠加的DyHead检测头更好地抵御环境噪声的干扰;最后,利用通道剪枝策略降低模型参数量。实验结果表明:在RUOD数据集上,改进后的模型有效的缓解了色偏、雾效应与光干扰等复杂水下环境下的漏检和误检现象,浮点数计算量降低8.4%
提高了水下设备在计算资源受到限制时的可用性。所提方法可适用于水下检测系统和水下机器人。
Zhang Qiming,Li Yang,Zhang Zhi,Yin Shibo,Ma Lin.Marine target detection for PPI images based on YOLO-SWFormer[J].Alexandria Engineering Journal,2023.
Fu Chenping,Liu Risheng,Fan Xin,Chen Puyang,Fu Hao,Yuan Wanqi,Zhu Ming,Luo Zhongxuan.Rethinking general underwater object detection: Datasets, challenges, and solutions[J].Neurocomputing,2023.
Zhang Yi-Fan,Ren Weiqiang,Zhang Zhang,Jia Zhen,Wang Liang,Tan Tieniu.Focal and efficient IOU loss for accurate bounding box regression[J].Neurocomputing,2022.
Zhao Shili,Zhang Song,Lu Jiamin,Wang He,Feng Yu,Shi Chen,Li Daoliang,Zhao Ran.A lightweight dead fish detection method based on deformable convolution and YOLOV4[J].Computers and Electronics in Agriculture,2022.
Lei Fei,Tang Feifei,Li Shuhan.Underwater Target Detection Algorithm Based on Improved YOLOv5[J].Journal of Marine Science and Engineering,2022.
Zheng Zhaohui,Wang Ping,Ren Dongwei,Liu Wei,Ye Rongguang,Hu Qinghua,Zuo Wangmeng.Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation.[J].IEEE transactions on cybernetics,2021.
Chen Lingyu,Zheng Meicheng,Duan Shunqiang,Luo Weilin,Yao Ligang.Underwater Target Recognition Based on Improved YOLOv4 Neural Network[J].Electronics,2021.
Lin Tsung-Yi,Goyal Priya,Girshick Ross,He Kaiming,Dollar Piotr.Focal Loss for Dense Object Detection.[J].IEEE transactions on pattern analysis and machine intelligence,2020.
Stefan Elfwing,Eiji Uchibe,Kenji Doya.Sigmoid-weighted linear units for neural network function approximation in reinforcement learning[J].Neural Networks,2017.
Ren Shaoqing,He Kaiming,Girshick Ross,Sun Jian.Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.[J].IEEE transactions on pattern analysis and machine intelligence,2017.
房鑫,陈兵旗,彭书博,张雄楚,李永正.基于改进YOLOv4的前方车辆检测方法[J].传感器与微系统,2024(10).
石健彤,王瑜,毕玉,肖洪兵,孙梅.基于注意力机制的特征融合孪生网络目标跟踪算法[J].传感器与微系统,2024(08).
杨卫,周丹丹,赵丹.我国数字经济和海洋经济高质量发展的耦合协调分析[J].海洋开发与管理,2023(07).
郝新泽,施一萍,邓源,秦瑶,刘瑾.基于轻量化YOLOv4的火灾检测识别算法[J].传感器与微系统,2023(08).
毛国君,翁伟栋,朱晋德,张媛,吴富村,毛玉泽.基于改进YOLO-V4网络的浅海生物检测模型[J].农业工程学报,2021(12).
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