參考文章：Han X, Leung T, Jia Y, et al. MatchNet: Unifying feature and metric learning for patch-based matching[C]. computer vision and pattern recognition, 2015: 3279-3286.

會議水平：CVPR 2015 （本家大哥賈揚清指導韓旭峰完成的，必須一讀）

?方法非常的簡單粗暴，完全不用看論文....

這里有一點還是值得學習的就是韓旭峰將各個通道的特征圖全部給打印出來了：

Visualization for the activations in response to an example input patch at different layers in the feature network. The input
64 × 64 patch is shown at the top. For each layer, we tile its K H × W activation maps to form a 2D image. H, W and K are
the height, width and depth of the 3D activation array respectively. Red margins separates these tiles. Pseudo-colors in the tiles represent response intensity. Border artifacts may occur, but we keep our padding scheme, which retrains half of the information on the original border

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