Computer Architecture Courses

Features in Computer Vision - Lecture 14

Explores local image features and interest points for matching images, stitching panoramas, and recovering structure from motion.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Training Neural Networks for Computer Vision - Part I - Lecture 10

Learn how convolutional neural networks are trained by minimizing loss with gradient descent, backpropagation, and stochastic gradient descent.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Introduction to Neural Networks for Computer Vision - Part I

An introduction to neural networks for image classification, covering pixel and feature representations, supervision, learning phases, and neural activation.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Edge Detection in Computer Vision - Part II - Lecture 7

Explains the Canny edge detector through gradients, orientation, non-maximum suppression, hysteresis thresholds, smoothing, and deep learning.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Edge Detection in Computer Vision - Part I - Lecture 6

Explores why edges matter in images and how filtering, smoothing, evaluation criteria, and derivative-based algorithms detect them, including human-face examples.

• YouTube
• 1 hour 11 minutes
• Self-Paced
• Free Video

Image Filtering in Computer Vision - Part II - Lecture 5

Explore image filtering through mean, weighted mean, Gaussian smoothing, box and median filters, Sobel filters, noise, and padded edges.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video

Basics of Linear Algebra for Computer Vision - Part II - Lecture 3

Introduces matrix operations and transformations—including determinants, inverses, scaling, and rotation—as mathematical foundations for computer vision.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Introduction to Computer Vision - Part II - Lecture 2

Survey of computer vision tasks from object recognition and segmentation to face identification, action recognition, and multi-object tracking.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Introduction to Computer Vision - Part I - Lecture 1

An introduction to computer vision connecting human visual perception with digital images, image understanding, retail analytics, and autonomous driving.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

From Saliency to Camouflage Analysis in Computer Vision

An overview of visual saliency methods and fully convolutional network approaches for detecting salient and camouflaged objects.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Introduction to Computer Vision - Lecture 1

An introduction to computer vision through the gap between human visual perception and machine-based image and video understanding.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

Introduction to Capsule Networks for Computer Vision

Explore capsule networks for computer vision through viewpoint equivariance, agreement-based object detection, dynamic routing, and EM routing.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Stereo Vision and Depth Perception in Computer Vision - Lecture 16

Learn how stereo image pairs produce depth maps through rectification, correspondence search, and correlation-based matching methods.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Mean Shift Algorithm for Computer Vision - Lecture 11

A computer vision lecture on mean shift, covering mean shift vectors and kernel profiles for tracking.

• YouTube
• 1 hour 6 minutes
• Self-Paced
• Free Video

Global Motion in Computer Vision - Lecture 9

Learn global motion estimation through coarse-to-fine optical flow, image warping, video mosaics, sprites, and projective transformations.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video