<ul><li>A CNN typically consists of the following layers: Max-Pooling, Average-pooling, Convolution layer, Fully Connected layer.</li><li>The output shape of a convolutional layer depends on the input shape, filter size, stride, and padding.</li><li>The number of parameters in a layer is determined by the number of filters, filter size, and the number of input channels.</li><li>CNNs have revolutionized the field of computer vision, enabling a wide range of applications.</li></ul>

Computer Vision 01: Demystifying CNNs: A Beginner’s Guide to Computer Vision

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