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Convolutional neural networks (CNNs) is widely used as classifiers in the field of computer vision. The more complex a CNNs model is, the more accurate classification results will be. But a very deep network also requires a better GPU to train and test in a reasonable time. In this paper, we purpose a tracking algorithm using LeNet-5, and avoid computing(More)
Image caption generation becomes a raising topic in computer vision and artificial intelligence. In order to solve the problem of stiff description, we intend to extract richer features using convolutional neural network (CNN). A neural and probabilistic framework has been proposed consequently which combines CNN with a special form of recurrent neural(More)
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