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Training constrained deconvolutional networks for road scene semantic segmentation
Training constrained deconvolutional networks for road scene semantic segmentation
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机译:训练约束反卷积网络进行道路场景语义分割
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摘要
A source deconvolutional network is adaptively trained to perform semantic segmentation. Image data is then input to the source deconvolutional network and outputs of the S-Net are measured. The same image data and the measured outputs of the source deconvolutional network are then used to train a target deconvolutional network. The target deconvolutional network is defined by a substantially fewer numerical parameters than the source deconvolutional network.
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