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
- Introduction to CNNs:
- Building a CNN from Scratch:
- Advanced CNN Architectures:
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:
- Research Papers:
Convolutional Neural Network
For more in-depth learning, check out our Deep Learning tutorials.