A Fast Identification Method for Vehicle Model Based on Improved YOLOv7-GCA
Aiming at the problems of high road traffic flow and slow model identification,a fast identification method for vehicle model based on improved YOLOv7-GCA is proposed.Firstly,the lightweight GhostConv with smaller parameter count and faster detection speed is used to replace the ordinary convolutional Conv in the network to im-prove the speed of vehicle model identification;secondly,in order to ensure the recognition accuracy of the model,the CA attention mechanism module is introduced before entering the neck.The experimental results show that the YOLOv7-GCA model reduces the number of parameters and complexity of the model and improves the vehicle mod-el recognition speed while ensuring the identification accuracy.
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