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# System prepended metadata

title: 03/31進度報告

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# 03/31進度報告
### 人臉辨識 

training data *40
![](https://i.imgur.com/f2zEx59.jpg =200x200)![](https://i.imgur.com/LN8FGXv.jpg =200x200)
![](https://i.imgur.com/BzSRBx5.jpg =200x200)![](https://i.imgur.com/TrdJSok.jpg =200x200)

testing data *40
![](https://i.imgur.com/VCN2wQl.jpg =200x200)![](https://i.imgur.com/kXLMomq.jpg =200x200)
![](https://i.imgur.com/3DTqgfr.jpg =200x200)![](https://i.imgur.com/HKZuDiO.jpg =200x200)

training data *157
![](https://i.imgur.com/aG34UIK.jpg =200x200)![](https://i.imgur.com/3UXlbfx.jpg =200x200)
![](https://i.imgur.com/d54OPcA.jpg =200x200)![](https://i.imgur.com/iHQqAme.jpg =200x200)

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### 接下來規劃
1.用face detection擷取臉部
2.第一種Data：training data使用上面的157張，testing data使用上面的測試40張
3.第二種Data：將157張裡面的照片分出約40張作為testing data，並補上40張測試照片進去

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### paper--> **Deep RNN Framework for Visual Sequential Applications**
http://openaccess.thecvf.com/content_CVPR_2019/papers/Pang_Deep_RNN_Framework_for_Visual_Sequential_Applications_CVPR_2019_paper.pdf