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(yáng)清指導(dǎo)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(diǎn)還是值得學(xué)習(xí)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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