
handle: 11012/138273
Image similarity measuring has many various applications. Pedestrian recognition is one of them and for the security purposes it is basically required to run in real-time. This paper proposes a deep Siamese neural network architecture for pedestrian recognition that achieves 70.28% accuracy on the test set containing 20 persons. Prediction of the model is fast enough for real-time processing.
Siamese, surveillance, deep learning, pedestrian, recognition
Siamese, surveillance, deep learning, pedestrian, recognition
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