Welcome to the introduction to Image Recognition course! This course will provide you with a comprehensive understanding of the fundamentals of image recognition and its applications in various fields.

Course Overview

  • Duration: 8 weeks
  • Level: Beginner to Intermediate
  • Prerequisites: Basic knowledge of Python and machine learning concepts

Course Content

  • Week 1: Introduction to Image Recognition

    • What is Image Recognition?
    • History and Evolution
    • Applications

  • Week 2: Image Preprocessing

    • Image Loading and Display
    • Image Resizing and Cropping
    • Image Grayscale Conversion

  • Week 3: Convolutional Neural Networks (CNNs)

    • CNN Architecture
    • Convolution and Pooling Layers
    • Activation Functions

  • Week 4: Deep Learning Frameworks

    • TensorFlow and Keras
    • Building and Training CNNs

  • Week 5: Image Classification

    • Training and Evaluating Models
    • Transfer Learning

  • Week 6: Object Detection

    • R-CNN, Fast R-CNN, and YOLO
    • Real-time Object Detection

  • Week 7: Image Segmentation

    • Semantic Segmentation
    • Instance Segmentation

  • Week 8: Project Work

    • Final Project Proposal
    • Project Execution and Presentation

Learning Outcomes

  • Understand the fundamentals of image recognition and its applications.
  • Learn to preprocess images and build CNNs using TensorFlow and Keras.
  • Implement and evaluate image classification, object detection, and image segmentation models.
  • Gain hands-on experience with real-world projects.

Additional Resources

For further reading and exploration, we recommend the following resources:

Convolutional Neural Network