Convolutional Neural Network (CNN) Tutorials

Dive deep into the world of Convolutional Neural Networks with our curated collection of tutorials. CNNs are a cornerstone of modern computer vision and are essential for tasks like image recognition, object detection, and image segmentation.

  • Introduction to CNNs

    Understand the fundamental building blocks of CNNs, including convolutional layers, pooling layers, and activation functions.

  • Building Your First CNN with TensorFlow

    A step-by-step guide to creating and training a simple CNN model for image classification using TensorFlow.

  • Image Recognition with PyTorch CNNs

    Learn how to implement CNNs in PyTorch for robust image recognition tasks, covering dataset preparation and model evaluation.

  • Advanced CNN Architectures

    Explore popular and powerful CNN architectures like ResNet, VGG, and Inception, and understand their underlying principles.

  • Transfer Learning with Pre-trained CNNs

    Leverage the power of pre-trained models for faster and more efficient development in your own computer vision projects.

  • Object Detection using Faster R-CNN

    An in-depth tutorial on implementing object detection models, specifically focusing on the Faster R-CNN architecture.

  • CNNs for Image Segmentation

    Learn how CNNs can be used to segment images at a pixel level, understanding architectures like U-Net.