Face detection based on the YOLOV2 algorithm can achieve a higher level of accuracy and show a faster detection speed. Therefore, the YOLOV2 algorithm appears more frequently in the field of target real-time detection. The traditional YOLOV2 algorithm uses the Darknet-19 network. Based on this, this paper builds a new network by merging the residual network (ResNet). In addition, in order to further make up for the defects exposed by the YOLOV2 algorithm in face detection, we change the weight of the loss function and implement an image enhancement scheme on the training set. The YOLOV2 algorithm and the improved YOLOV2 algorithm are compared and tested on the Wider Face dataset, and then we use face data sets from different angles to test the performance of the algorithm. According to the analysis of the experimental results, the improved YOLOV2 algorithm can show higher accuracy and robustness in multi-angle face detection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.