Roadside vehicle sensing method based on SSD improved algorithm

The invention belongs to road cooperation roadside end vehicle detection, and particularly relates to a roadside end vehicle sensing method based on an SSD (Solid State Disk) improved algorithm, which is used for improving the accuracy and robustness of a model through a mosaic mosaic online data enhancement algorithm based on a caffe framework SSD. An improved feature extraction module based on a cross-stage partial connection mode and resnet18 residual connection fusion has stronger feature expression ability, and the time consumption of forward calculation is reduced. Based on an SSD detection algorithm of a caffe framework, a positioning loss function is improved, a Complete-IOU positioning loss function is fused, the accuracy of a detection frame is improved, and the model is enabled to converge more quickly. 本发明属于路协同路侧端的车辆检测，特别是涉及一种基于SSD改进算法的路侧端车辆感知方法，其通过基于caffe框架SSD的马赛克mosaic在线数据增强算法，以提高模型的准确率和鲁棒性。改进的基于跨阶段部分连接方式和resnet18的残差连接融合的特征提取模块，具有更强的特征表达能力，减少前向计算耗时。基于caffe框架的SSD检测算法，改进定位损失函数，融合Complete-IOU定位损失函数