A very simple explanation of convolutional neural network or CNN or ConvNet such that even a high school student can understand it easily. This video involves very less math and is perfect for total beginner who doesn't have any idea on what CNN is and how it works. We will cover different topics such as,
1. Why traditionally humans are better at image recognition than computers?
2. Disadvantages of using traditional artificial neural network (ANN) for image classification.
3. How human brain recognizes images?
4. How computers can use filters for feature detection
5. What is convolution operation and how it works
6. Importance of ReLU activation in CNN
7. Importance of pooling operation in CNN
8. How to handle rotation and scale in CNN
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Here are some good articles on CNN,
Is CNN scale/rotation invariant?
https://stats.stackexchange.com/questions/239076/about-cnn-kernels-and-scale-rotation-invariance#:~:text=22-,1)%20The%20features%20extracted%20using%20CNN%20are%20scale%20and%20rotation,details%2C%20see%3A%20Deep%20Learning.&text=Convolution%20is%20not%20naturally%20equivariant,or%20rotation%20of%20an%20image.
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
PDF Paper on cnn: http://www.deeplearningbook.org/contents/convnets.html
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