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Computer Vision Part 2: Algorithms
Pre-module reading list
Introduction
Introduction [06:06]
Overview [15:28]
Main advances and challenges in the field [18:48]
Basic Theory
The role of deep learning in computer vision [12:42]
Key Terms [04:34]
Sample Chapter
Camera sensors [07:36]
Protective Geometry [13:18]
Camera calibration [09:19]
Perception Tasks
Image transformations [11:02]
Object detection [22:02]
Depth estimation [13:11]
Optical Flow [11:01]
Object tracking [21:56]
Drivable surface estimation and lane detection [11:41]
Semantic segmentation, instance segmentation, and panoptic segmentation [35:38]
Multimodal Perception
Visual odometry [18:08]
End of module tasks
Fusion techniques for perception tasks [15:56]
Module exercises
End of module reading list
Computer Vision Algorithms Quiz
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Computer Vision Part 2: Algorithms
Key Terms [04:34]
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