Vehicle Detection Method Based on GhostNet SSD
The traditional vehicle target detection algorithm needs to select appropriate features for different image scenes, resulting in poor generalization ability. In order to solve this problem, this paper proposes an image vehicle detection method based on SSD. This method combines GhostNet and SSD to extract feature maps from GhostNet for classified and location prediction. To some extent, the detection accuracy and speed of the vehicle are improved. Experimental results show that this method has a high recognition rate and is better than the traditional algorithm.
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)