基于YOLOv5s和双稳随机共振的夜间车辆检测算法  

Night Vehicle Detection Algorithm Based on YOLOv5s and Bistable Stochastic Resonance

作　　者：胡鹏飞 王友国[1,2] 翟其清[1] 颜俊[2] 柏泉 HU Pengfei;WANG Youguo;ZHAI Qiqing;YAN Jun;BAI Quan(School of Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China;School of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)

机构地区：[1]南京邮电大学理学院,南京210023 [2]南京邮电大学通信与信息工程学院,南京210023

出　　处：《计算机科学》2024年第9期173-181,共9页Computer Science

基　　金：国家自然科学基金(62071248)。

摘　　要：针对夜间车辆检测过程中光照不强导致漏检误检的问题,基于YOLOv5s和双稳随机共振提出一种改进的夜间车辆检测算法。YOLOv5s从4方面进行改进:1)在Backbone和Neck中更换细小结构,提高网络对小目标的检测能力;2)加入由坐标注意力CA和能量注意力SimAM构成的双注意力机制,提高网络对目标的特征提取能力;3)采用轻量化骨干Fasternet,减少模型参数量;4)在Head中采用WIoU损失函数,加快边界框回归损失的收敛速度。利用经典的双稳随机共振对夜间车辆数据集进行低照度图像增强,分析其有效性,并将增强后的夜间车辆图像传入改进的YOLOv5s网络进行训练。实验结果表明,相较于原始YOLOv5s,融合改进的YOLOv5s和双稳随机共振的夜间车辆检测算法在执行远景小目标以及密集遮挡的夜间车辆检测任务时具有更高的准确率和更低的漏检率。Aiming at the problems of missed and false detection caused by weak illumination during night vehicle detection,an improved night vehicle detection algorithm is proposed based on bistable stochastic resonance and YOLOv5s.YOLOv5s is improved from four aspects,replacing small structures in Backbone and Neck to improve the detection ability of the network to small targets.A dual attention mechanism composed of coordinate attention CA and energy attention SimAM is added to improve the feature extraction ability of the network to the target.The lightweight backbone Fasternet is adopted to reduce the amount of model parameters.The WIoU loss function is used in Head to accelerate the convergence speed of bounding box regression loss.The effectiveness of the nighttime vehicle dataset is analyzed from quantitative and qualitative perspectives by using classical bistable stochastic resonance,and the enhanced nighttime vehicle images are passed into the improved YOLOv5s network for training.Experimental results show that,compared with the original YOLOv5s,the night vehicle detection algorithm combining improved YOLOv5s and bistable stochastic resonance has better accuracy and lower missed detection rate when performing long-range small targets and densely occluded night vehicle detection tasks.

关 键 词：双稳随机共振 低照度图像增强 YOLOv5s 双注意力机制 轻量化骨干 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]