Convolutional Neural Network: Feature Map and Filter Visualization

Learn how Convolutional Neural Networks understand images.

In this article, we will visualize the intermediate feature representations across different CNN layers to understand what happens inside CNN’s to classify images.

Prerequisites:

Convolutional Neural Network Basics,

Building Powerful Image Classification Convolutional Neural Network using Keras

Building powerful image classification CNN using Keras

A quick overview of CNN

Supervised Deep Learning and Machine Learning take data and results as an input during training to generate the rules or data patterns. Understanding of data patterns or rules generated by the model helps us understand how the results were derived from the input data.

Training: Convolutional neural network takes a two-dimensional image and the class of the image, like a cat or a dog as an input. As a result of the training, we get trained weights, which are the data patterns or rules extracted from the images.

Inference or Prediction: Image will be the only input passed to the trained model, and the trained model will output the class of the…