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- W2782084893 abstract "A new methodology for image synthesis based on two cooperative training ConvNets is proposed. Two generative ConvNets and unsupervised joint learning are designed to effectively reflect the characteristics of real scenery and image pattern. Every ConvNet is directly derived from the discriminate ConvNet and has the potential to learn from big unlabeled data, either by contrastive divergence. One ConvNet maps the observed image to the feature statistics. and the other maps the latent factors to the observed image. The model is generative in the sense that images can be generated from the probability distribution defined. An experimental evaluation of the proposed approach has been made on publicly available datasets. For natural image patterns, the results of the new technique look subjectively better." @default.
- W2782084893 created "2018-01-12" @default.
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- W2782084893 date "2017-10-01" @default.
- W2782084893 modified "2023-09-23" @default.
- W2782084893 title "Synthesis of image patterns based on cooperative training convnet" @default.
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- W2782084893 doi "https://doi.org/10.1109/cac.2017.8243746" @default.
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