Deep RNN Framework for Visual Sequential Applications
Deep RNN Framework for Visual Sequential Applications 來自2019CVPR 上海交大 彭博的論文。 改論文主要面對的問題是 1.RNN網絡的深度與RNN的細胞數遲矛盾關係 2.RNN層數過深導致在訓練時精度下降 3.RNN增加參數量增加明顯 主要貢獻： 1.提出了一個新的模型CBM Context Bridge Module 2.提出了一種平滑
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相關文章
- 1. Inspirational Applications of Deep Learning
- 2. A PMML Based Framework for Developing R-Java Analytic Applications
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- 5. 雙向RNN&Deep RNN
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- 9. PEAX: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Le
- 10. CNN-RNN: A Unified Framework for Multi-label ImageClassification