基于卷积神经网络的目标识别算法研究

Research on Target Recognition Algorithm Based on Convolutional Neural Network

随着时代的快速发展,对于监控视频处理,传统人工处理方式已不能满足社会实际发展需求。智能监控依靠目标检测实现监控,目标识别成为计算机视觉领域的重要研究方向,主要从图像或者视频中检测某一类别的目标。基于此,分析卷积神经网络目标识别算法,研究目标检测算法存在的问题,并提出相应对策,有效提高检测算法的有效性和精确度,从而推动智能视频监控的快速发展和广泛应用。

With the rapid development of the times, for surveillance video processing, traditional manual processing methods can not meet the actual needs of social development. Intelligent surveillance relies on target detection to achieve surveillance. Target recognition has become an important research direction in the field of computer vision. It mainly detects a certain category of targets from images or videos. Based on this, the convolutional neural network target recognition algorithm is analyzed, the existing problems of target detection algorithm are studied, and the cor responding countermeasures are put forward to effectively improve the effectiveness and accuracy of detection algorithm, thus promoting the rapid development and wide application of intelligent video surveillance.