In this post, we are going to understand what a convolutional neural network is and how it works. I’ll be explaining how all the layers are stacked together to form specific architectures. At the end of this post, you will be able to train and test your own convolutional neural network in your own dataset.
I grouped all the information needed to understand what a Convolutional Neural Network is and how it works. This post answers all the questions that I once had when I first started to study CNN and I decided to put them all together.
In the end, I attached the code needed to train your own CNN using Keras. The code is very intuitive and you will easily understand after reading the entire post.
Convolutional neural networks
Convolutional neural networks or just CNNs are a type of deep learning used for image recognition (more correctly “image classification” because it classifies the image into probabilistic classes) and object detection (detecting the coordinates of an object in an image), different architectures are used depending on the aim, for object classification we use Google Inception Net, VGG Net, Let Net, etc. For object detection, we use Single Shot Detectors or YOLO.
David Mata blog 