有没有办法在张量流中向conv2d添加规范化 [英] Is there way to add normalization to conv2d in tensorflow

问题描述

为了正确进行模式匹配，卷积需要规范化
https ：//en.wikipedia.org/wiki/Cross-correlation#Normalized_cross-correlation

in order to do pattern matching properly convolutions require normalization https://en.wikipedia.org/wiki/Cross-correlation#Normalized_cross-correlation

不幸的是，我找不到一种方法来使输入标准化

unfortunately I can't find a way how to make input normalization for conv2d function.

是否隐藏在实现中？

推荐答案

原来，我正在寻找tf.local_response_normalization（ https： //www.tensorflow.org/versions/r0.11/api_docs/python/nn/normalization ）出于某种奇怪的原因，它出现在conv2层之后，并且在示例中很少使用

It turned out, I was looking for tf.local_response_normalization (https://www.tensorflow.org/versions/r0.11/api_docs/python/nn/normalization) for some strange reason it goes after conv2 layers and used not very often in examples

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