文件名称：Multi-column deep neural network for traffic sign classification
文件大小：1.57MB
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更新时间：2021-03-24 06:53:45
Deep neural networks
交通信号灯识别We describe the approach that won the final phase of the German traffic sign recognition benchmark. Our method is the only one that achieved a better-than-human recognition rate of 99.46%. We use a fast, fully parameterizable GPU implementation of a Deep Neural Network (DNN) that does not require careful design of pre-wired feature extractors, which are rather learned in a supervised way. Combining various DNNs trainedon differently preprocessed data into aMulti-Column DNN (MCDNN) further boosts recognition performance, making the system insensitive also to variations in contrast and illumination.