Convolutional Neural Networks (CNNs) are a class of deep neural networks that are particularly effective for analyzing visual imagery. This page provides examples and tutorials on CNNs in the field of AI.
CNN Basics
- What is a CNN? A CNN is a deep learning algorithm that can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image, and be able to differentiate between different kinds of images.
- Applications CNNs are widely used in image recognition, object detection, and other areas of computer vision.
Example Tutorials
- Deep Learning with CNNs
- This tutorial provides a comprehensive introduction to CNNs, including their architecture, training, and applications.
- Building a CNN from Scratch
- Learn how to build a CNN from scratch using Python and TensorFlow.
CNN Images
Here are some examples of images that CNNs can be trained on:
Conclusion
CNNs are powerful tools for analyzing visual imagery. By following the tutorials and examples provided on this page, you can gain a deeper understanding of how CNNs work and how they can be applied to various tasks.