基于改进的SSD模型手机违规使用目标检测*

针对某些对手机使用有特殊规定的场所时常面临难以准确、高效地识别手机违规使用的问题,提出了一种基于改进的SSD模型来检测手机的违规使用.利用SSD模型获取初次目标位置及区域分类,并利用改进的DenseNet模型对初次目标框进行判定,从而获得精确的手机检测边界框.为改进数据预处理流程,采用了数据扩增与图像质量改善相结合的策...

Target detection of illegal use of mobile phone based on improved SSD model

In order to solve the problem that it is difficult to identify the illegal use of mobile phones accurately and efficiently in some places with special regulations on mobile phone use, this paper proposes an improved SSD model to detect the illegal use of mobile phones. The SSD model is used to obtain the location and area classification of the primary target, and the improved DenseNet model is used to determine the primary target frame, so as to obtain the accurate mobile phone detection boundary box. In order to improve the data preprocessing process, the strategy of combining data amplification with image quality improvement is adopted. The experimental results on the mobile phone set built by ourselves verifying the effectiveness of these improved strategies. The location accuracy of the improved SSD model can reach 91.1%, and the recognition accuracy can reach 98%, which is 35% higher than the original SSD model. The improved SSD model has the characteristics of high recognition accuracy and high positioning accuracy, which can provide theoretical basis and technical support for intelligent recognition of illegal use of mobile phones.