CNN Models Overview

CNN, or Convolutional Neural Networks, are a class of deep neural networks that are particularly effective for analyzing visual imagery. Below, we'll explore some of the most popular CNN models used in the field of computer vision.

Popular CNN Models

Here are some of the most widely used CNN models:

• AlexNet: This was one of the first CNNs to win the ImageNet competition and kickstarted the deep learning revolution.
• VGGNet: Known for its simplicity and effectiveness, VGGNet uses a stack of convolutional layers.
• ResNet: ResNet introduced the concept of residual learning, allowing for much deeper networks without the vanishing gradient problem.
• Inception: Inception models use a network of inception modules that allow for multiple convolutional filters at each scale.

Learning Resources

For those looking to delve deeper into CNNs, here are some resources:

• Deep Learning Specialization by Andrew Ng
• Convolutional Neural Networks - Our tutorial on CNNs with practical examples.

Images

Here are some images representing different CNN architectures: