Attention[Content]

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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

来源：https://www.cnblogs.com/shouhuxianjian/p/7903097.html