Deep RNN Framework for Visual Sequential Applications
Deep RNN Framework for Visual Sequential Applications 来自2019CVPR 上海交大 彭博的论文。 改论文主要面对的问题是 1.RNN网络的深度与RNN的细胞数迟矛盾关系 2.RNN层数过深导致在训练时精度下降 3.RNN增加参数量增加明显 主要贡献： 1.提出了一个新的模型CBM Context Bridge Module 2.提出了一种平滑
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相关文章
- 1. Inspirational Applications of Deep Learning
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