---
# System prepended metadata

title: CNN

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# CNN
捲積
![](https://i.imgur.com/K9NhhGn.jpg)
![](https://i.imgur.com/DvRKz2R.png)
![](https://i.imgur.com/fX2bQ3m.png)
池化
![](https://i.imgur.com/iX3d2Bp.jpg)
![](https://i.imgur.com/pd2WIs7.png)

yolact
![](https://i.imgur.com/d0htHV2.png)


FPN
C1做捲積(降採樣)
視覺感受變大


P3-->P4做反捲積(升採樣)
解析度變高

C3跟C4做疊合，得到更多的細節

![](https://i.imgur.com/76NR1QP.png)
左邊 捲積 降採樣
右邊 反捲積 升採樣
![](https://i.imgur.com/jhLapxI.png)
![](https://i.imgur.com/cWOkLrZ.png)
Anchor
![](https://i.imgur.com/UZaOBBQ.png)




 resulting in the scales [24, 48, 96, 192, 384]
![](https://i.imgur.com/NAyUfg0.png)
x
nms
![](https://i.imgur.com/fRI7WaJ.png)

pi是幾層P構成的
左邊是原來的retinaNet
本來只輸出class跟 box cordinate anchor aspect ratio(a)


| class | box | 
| -------- | -------- | 
| class&score    | box cordinate&confidence score   |


yolact

| class | box | mask |
| ------------ | -------- | -------- |
| class&score&anchor| box cordinate&confidence score&anchor     | k mask coefficent     |

![](https://i.imgur.com/dn9WO2y.png)
protonet會產生很多的prototype

之後在做prototype跟mask coefficient 係數相乘


crop
做切割

threshold

邊緣檢測後找出找出完整樣本 2天
斜率檢測製圖演算法開發 4天
水平雜訊過濾演算法開發 3天
垂直雜訊過濾演算法開發 5天
特徵檢測演算法開發 5天
水平座標排序法開發 2天
樣本驗證與演算法最佳化調整 7天
影片合成 1天

