An introduction to the basic concepts and building blocks of Convolution Neural Networks CNNs covering theory, best practices and practical widgets.
Interactive calculator to compute the output shape of a convolutional layer based on the input, kernel and other settings. It supports non-square kernels, stride and padding.
Let's dive into the paper 'ImageNet Classification with Deep Convolutional Neural Networks' by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton, which introduced the AlexNet to the world, and became a pivotal moment in the fields of computer vision and deep learning. The goal here is to explore in-depth the achievements, architecture, and details as a previous step toward its implementation.