Course 9: Computer Vision
- 6 months
- Intakes: Jan, Apr, Jun, Oct
Prerequisites
- Math knowledge (Statistics and Probability, linear algebra, and calculus)
- Knowledge of basic machine learning
- Programming Knowledge – Python
- Tensorflow or Pytorch knowledge
Who is this course for?
- Students who complete the Tensorflow and/or Pytorch course and Basic AI and ML course and want to advance more.
- Students who have not studied Computer Vision.
- People who want to start their AI career specializing in Computer Vision field.
What you'll get after completeing this course:
Camera and Imaging
- Image Formation
- Image Sensing
- Binary Images
- Image Processing
Features and Boundaries
- Edge Detection
- Boundary Detection
- SIFT Detector
- Image Stitching
- Face Detection
3D Reconstruction – Single Viewpoint
- Getting Started: 3D Reconstruction – Single Viewpoint
- Radiometry and Reflectance
- Photometric Stereo
- Shape from Shading
- Depth from Defocus
- Active Illumination Methods
3D Reconstruction – Multiple Viewpoints
- Camera Calibration
- Uncalibrated Stereo
- Optical Flow
- Structure from Motion
Visual Perception
- Object Tracking
- Image Segmentation
- Appearance Matching
- Neural Network
How to Apply?
- You Apply
Tell us a little about yourself and we’ll help with the rest. Our convenient online application tool only takes 10 minutes to complete.
- We Connect
After you submit your application, an admissions representative will contact you and will help you to complete the process.
- You Get Ready
Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.