Attention[Content]


0. 引言

神经网络中的注意机制就是参考人类的视觉注意机制原理。即人眼在聚焦视野区域中某个小区域时,会投入更多的注意力到这个区域,即以“高分辨率”聚焦于图像的某个区域,同时以“低分辨率”感知周围图像,然后随着时间的推移调整焦点。

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  17. [Blog] - .Attention and Augmented Recurrent Neural Networks
  18. [Quora] - .How-does-an-attention-mechanism-work-in-deep-learning
  19. [Quora] - .Can-you-recommend-to-me-an-exhaustive-reading-list-for-attention-models-in-deep-learning
  20. [Quora] - .What-is-attention-in-the-context-of-deep-learning
  21. [Quora] - .What-is-an-intuitive-explanation-for-how-attention-works-in-deep-learning
  22. [Quora] - .What-is-exactly-the-attention-mechanism-introduced-to-RNN-recurrent-neural-network-It-would-be-nice-if-you-could-make-it-easy-to-understand
  23. [Quora] - .How-is-a-saliency-map-generated-when-training-recurrent-neural-networks-with-soft-attention
  24. [Quora] - .What-is-the-difference-between-soft-attention-and-hard-attention-in-neural-networks
  25. [Quora] - .What-is-Attention-Mechanism-in-Neural-Networks
  26. [Quora] - .How-is-the-attention-component-of-attentional-neural-networks-trained
posted @ 2018-03-22 11:31 仙守 阅读(...) 评论(...) 编辑 收藏