Vehicle Logo Recognition Based on Convolutional Neural Networks
Proposes a vehicle logo recognition based on Convolutional Neural Networks.With a deep hierarchical feature learning process,the proposed method extracts the features from the training samples directly,and trains the classier based on neural network.Applies 5,000 logos belonging to 10 vehicle manufactures for validation.The average accuracy 98.28%for ten classes and fast implementation (less than 3ms for each logo in MATLAB) has demonstrated that the proposed method outperforms than state-of-art with higher accuracy,stronger robustness,and less computational cost.
Intelligent Transportation SystemsVehicle Logo RecognitionDeep LearningConvolutional Neural Networks
NETL
NSTL
万方数据
维普
