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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Convolutional Deep Belief Networks ： ウィキペディア英語版 Convolutional Deep Belief Networks In computer science, Convolutional Deep Belief Network (CDBN) is a type of deep artificial neural network that is composed of multiple layers of convolutional restricted Boltzmann machines stacked together. Alternatively, it is a hierarchical generative model for deep learning, which is highly effective in the tasks of image processing and object recognition, though it has been used in other domains too. The salient features of the model include the fact that it scales well to high-dimensional images and is translation-invariant.〔(【引用サイトリンク】first=Emanuele )〕 CDBNs use the technique of probabilistic max-pooling to reduce the dimensions in higher layers in the network. Training of the network involves a pre-training stage accomplished in a greedy layer-wise manner, similar to other deep belief networks. Depending on whether the network is to be used for discrimination or generative tasks, it is then "fine tuned" or trained with either back-propagation or the up-down algorithm, respectively ==References== 〔 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Convolutional Deep Belief Networks」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.