Here’s our detailed Computer Vision Course Curriculum and syllabus. We will cover all these topics and more in Computer Vision Courses Syllabus and outline:

  1. Introduction to Computer Vision
    1. Basic Concepts
    2. Image Filtering Techniques

  2. Human Visual System


  3. Feature Detection and Matching Techniques
    1. Edge Detection
    2. Corner Detection
    3. Discriminative Interest Point Detectors
    4. Interview Questions and Preparation
  4. Camera Models and 3D Computer Vision
    1. Camera Calibration
    2. Stereo Vision
    3. Generating 3D images from 2D views (exciting, isn’t it?)
    4. Interview Questions and Preparation
  5.  Machine Learning Fundamentals
    1. Supervised Learning
      1. Feature selection and learning
      2. Classification Techniques
      3. Generative and Discriminative Models (GANs)
    2. Semi-supervised Learning
    3. Unsupervised Learning
    4. Self-Supervised Learning
    5. Interview Questions and Preparation
  6. Deep Learning 
    1. Introduction to Convolutional Neural Network
    2. CNN Artchitecture: DenseNET, ResNET, Fully Convolutional Networks
    3. Interview Questions and Preparation
  7. Object Detection
    1. RCNN, Fast-RCNN, Faster RCNN, Mask RCNN
    2. YOLO, SSD for Object Detection
    3. Feature Pyramid Networks
    4. EfficientDet
    5. Interview Questions and Preparation
  8. Image Segmentation
    1. UNET
    2. Fast FCN
    3. Gated SCNN
    4. DeepLab
    5. Interview Questions and Preparation
  9. Object Tracking
    1. Single and Multiple Object Tracking using deep learning
  10. Medical Image Diagnosis
    1. Tissue, bone and muscle segmentation in X-ray, CT and MRI
    2. Automatic cancer detection in liver, pancreas, brain, kidney, lung and other organs
    3. Radiologists in the loop systems
  11. Action Recognition
    1. Review of state-of-the-art action recognition systems
  12. Applications in Retail and E-Commerce
    1. Image search, retrieval and recommendation systems
  13. Autonomous Driving


  14. Exciting Applications in Astronomy and other fields


  15. Building a Computer Vision Startup


  16. Review and Final project