关键词: 卷积神经网络, MTCNN, 检测网络, YOLOv3, 目标分割, SSD300

Abstract: Traditional detection networks have always had problems of low detection efficiency and low accuracy in complex backgrounds. Aiming at the above problems, this paper further designs the MT-Siam network based on the MTCNN algorithm, which mainly provides accurate position positioning for the independent segmentation of single target, image processing of single target and other operations in the future, so as to quickly obtain the target position and achieve the purpose of improving the detection efficiency. In the experiments, a comprehensive comparison is made on the basic model of YOLOv3, SSD300 and MTCNN to verify the superiority of MTCNN network. The comparative experiments show that, compared with MTCNN, the proposed MT-Siam algorithm can improve the detection speed by 70% to 85% while maintaining high precision.

Key words: convolutional neural network, MTCNN, detection network, YOLOv3, target segmentation；SSD300