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Very Deep Convolutional Networks for Text Classification
時間 2020-12-24
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實現:https://github.com/zonetrooper32/VDCNN Abstract NLP的許多任務的方法是循環神經網絡,特別是LSTM,與深層的卷積神經網絡相比,這些網絡都比較淺,所以我們構建VDCNN,這是字符級的,並且僅用小的卷積和pooling操作,用了29層卷積層。 1 Introduction NLP的任務是處理文本,提取文本,採用不同形式表示相同的信息,我們希望把標
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相關文章
1.
(35) [arXiv17] Very Deep Convolutional Networks for Text Classification
2.
Very Deep Convolutional Networks for Text Classification之每日一篇
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《Character-level Convolutional Networks for Text Classification》
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Graph Convolutional Networks for Text Classification
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Recurrent Convolutional Neural Networks for Text Classification
6.
Very Deep Convolutional Networks for Large-Scale Image Recognition
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VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
8.
VGG: VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
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