Convolutional Neural Network (CNN) Tutorials

Convolutional Neural Networks (CNNs) are a class of deep neural networks that are particularly effective for analyzing visual imagery. They are widely used in fields like image recognition, object detection, and medical image analysis. This page is dedicated to tutorials and resources on CNNs.

Basic Concepts

• Neural Networks: The foundation of CNNs.
• Convolutional Layers: The core of CNNs.
• Pooling Layers: Reduces the spatial dimensions of the input volume for computational efficiency.

Tutorials

1. Introduction to CNNs:
   • A Gentle Introduction to CNNs
2. Building a CNN from Scratch:
   • Step-by-Step Guide to Building a CNN
3. Advanced CNN Architectures:
   • Understanding Advanced CNNs

Practical Examples

• Image Recognition: CNNs are highly effective in recognizing objects in images.
• Object Detection: Detecting and classifying objects in real-time video streams.
• Medical Image Analysis: Diagnosing diseases using medical images.

Resources

• Books:
  • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
• Online Courses:
  • Coursera's Convolutional Neural Networks
• Research Papers:
  • AlexNet: Image Classification with Deep Convolutional Neural Networks

Convolutional Neural Network

For more in-depth learning, check out our Deep Learning tutorials.