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# System prepended metadata

title: CNNA

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# CNNA
[NOTES](https://community.deeplearning.ai/t/course-4-lecture-notes/11879)
## Basics

![](https://i.imgur.com/NHlmsIE.png)
![](https://i.imgur.com/Aiaajuk.png)
![](https://i.imgur.com/tFpvu7T.png)
![](https://i.imgur.com/0m0O9p4.png)

## 1 layer CN
![](https://i.imgur.com/mV43EYU.png)
![](https://i.imgur.com/CzxVoYt.png)
![](https://i.imgur.com/3tDxS72.png)

## Pooling
No parameters to learn!!!!!!!!!!!!!!
![](https://i.imgur.com/oNi2JDd.png)
![](https://i.imgur.com/GH0VYHe.png)
![](https://i.imgur.com/BWDgWNM.png)


## Neural Network with convolution
![](https://i.imgur.com/4hObICV.png)
![](https://i.imgur.com/aACrETF.png)
![](https://i.imgur.com/abbUcaA.png)

## CNN Networks
### LeNet
![](https://i.imgur.com/OPcCKyB.png)

### AlexNet
![](https://i.imgur.com/K5kpqB6.jpg)

### VGG
![](https://i.imgur.com/DdEJMeO.png)

### ResNet
![](https://i.imgur.com/mg2TL1T.png)
![](https://i.imgur.com/dSPUewl.jpg)
![](https://i.imgur.com/VczQ4c4.png)

### Networks in Networks (1x1 convo)
![](https://i.imgur.com/bksyP3Z.png)

### Inception
![](https://i.imgur.com/r41gocj.png)
![](https://i.imgur.com/FjPQVGq.png)
![](https://i.imgur.com/pKR3VqU.png)

![](https://i.imgur.com/Cge3mqj.png)
### GooleNet
![](https://i.imgur.com/Dk0Ic5O.png)

### MobileNet

Less params
![](https://i.imgur.com/DfaPzGW.png)
![](https://i.imgur.com/9GJIyvK.png)
![](https://i.imgur.com/dLM7oeE.png)

### Transfer learning
![](https://i.imgur.com/FHvokSe.png)
### Data augmentation
![](https://i.imgur.com/KDXKjoG.png)
![](https://i.imgur.com/TSQW0tH.png)

## Object Localization
![](https://i.imgur.com/RX0SsVw.png)
![](https://i.imgur.com/6HP6qaP.jpg)
### Landmark Detection
![](https://i.imgur.com/EJisVJx.png)

### Object Detection
![](https://i.imgur.com/UbVqDQC.png)
![](https://i.imgur.com/vWGvN0B.png)
#### Conv implementation
![](https://i.imgur.com/J4rd81T.png)
![](https://i.imgur.com/U2Dq68m.jpg)
![](https://i.imgur.com/lIGiGVT.png)

### Bounding Box Prediction
![](https://i.imgur.com/4IVWXSt.png)
![](https://i.imgur.com/oFkf27N.png)

### IOU
![](https://i.imgur.com/5EGDygQ.png)

### Non max Supression 
clears out multiple pred
![](https://i.imgur.com/FZUOZbf.png)

### Anchor Box
![](https://i.imgur.com/xhC6nxP.png)
![](https://i.imgur.com/lUekyzv.png)
![](https://i.imgur.com/HjUKjWy.png)

### YOLO
![](https://i.imgur.com/B9jN1me.png)
![](https://i.imgur.com/vJxIUbm.png)
![](https://i.imgur.com/QVTou9b.png)

### RCNN
Instead of sliding through whole img slide through required area only
![](https://i.imgur.com/wl136tq.png)
![](https://i.imgur.com/hXvsU49.png)

## Semantic Segmentation
![](https://i.imgur.com/wAPpavO.png)
![](https://i.imgur.com/ZC55Ycn.png)
U-Net algo is used for segmentation
![](https://i.imgur.com/xK1hFGS.png)



### Transpose Convo
![](https://i.imgur.com/wfulgM2.png)

### UNet
low level by skip conn
high level by network
![](https://i.imgur.com/5jQ0zmc.png)
![](https://i.imgur.com/5cWpdqW.png)
![](https://i.imgur.com/azc1qw4.png)

## FACE RECOGNITION
![Uploading file..._crw9bt7zi]()

### One shot learning
![Uploading file..._6w0ol3wxj]()

![Uploading file..._rq46224ut]()

