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A method of training a convolution recurrent neural network and a semantic segmentation method of an input video using a trained convolutional recurrent neural network
A method of training a convolution recurrent neural network and a semantic segmentation method of an input video using a trained convolutional recurrent neural network
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机译:一种训练卷积复发性神经网络的方法和使用训练卷积复制神经网络的输入视频的语义分割方法
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摘要
PROBLEM TO BE SOLVED: To provide a method for training a convolutional recurrent neural network for the semantic segmentation of a video.;SOLUTION: The method includes the steps of: training a first convolutional neural network using a set of semantically segmented training images; and training a convolutional recurrent neural network that corresponds to the first convolutional neural network using a set of semantically segmented training videos. The convolution layer is substituted for by a recurrent model having a hidden state. The step for training the recurrent neural network includes a step for warping the internal state of a recurrent layer by an optical flow estimated for the contiguous frame pairs t-1, t of the training video set so that the internal state adapts to pixel motion between paired frames, and a step for learning at least the recurrent module.;SELECTED DRAWING: Figure 4;COPYRIGHT: (C)2020,JPO&INPIT
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