Improved Object Detection Algorithm for YOLOv7 in Complex Driving Environments
In order to solve the problems of false detection and missed detection caused by the existing object detec-tion algorithms,an improved object detection method in complex driving environment is proposed based on YOLOv7.Firstly,CBAM attention mechanism is introduced into the original model to suppress background interference information.Secondly,NWD is used as the loss function of the algorithm to enhance the detection ability of small object.Experimental results show that,on the public data set KITTI,the accuracy rate is improved by 4.5%compared with the original algorithm.
万方数据
维普
