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In chapter 1 we learned about neural network with python, now let’s move a bit towards CNN (Convolutional Network Network). This chapter is 2.1 because we will only talk about CNN in more theoretical way, just to understand what is going on here. So here is the plan of attack:
- Introduction
- What is CNN?
- How Does a CNN Work?
- Input
- Convolution
- Stride
- Padding
- Pooling
- Flattening
- Fully Connected Layers
- Output
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Introduction
In the ever-evolving world of artificial intelligence and deep learning, Convolutional Neural Networks (CNNs) have become a cornerstone for various applications, especially in the field of computer vision. CNNs are powerful tools designed to mimic the human visual system and are exceptionally adept at recognizing patterns in images and videos. Today’s ResNets series, SAM, YOLOv8 etc. are build on CNN blocks. Figure 1 shows the example of CNN (Convolutional Neural Network).
What is CNN?
At its core, a Convolutional Neural Network is a type of artificial neural network, which means it’s a computational model inspired by the way the human brain processes information. However, CNNs are…