Computer Architecture Courses

Motion Models in Computer Vision - Lecture 8

Learn about optical flow, rotation, image formation, and 3D rigid motion in computer vision. Explore displacement models and projective transformations using point correspondences.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Optical Flow in Computer Vision - Lecture 6

Learn about optical flow in computer vision, covering applications, optimization problems, Laplacians, and solutions, with practical examples and in-depth explanations.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Edge Detection in Computer Vision - Lecture 3

Explore edge detection techniques in computer vision, including Marr-Hildreth and Canny methods. Learn about 2-D Gaussian filters, zero crossings, and hysteresis thresholding for improved image analysis.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Filtering in Computer Vision - Lecture 2

Learn about image filtering techniques, including noise reduction, edge detection, and smoothing. Explore applications in computer vision and gain hands-on experience with MATLAB functions for image processing.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video

Introduction to Computer Vision - Lecture 1

Explore fundamental concepts of computer vision, including image processing, object detection, and facial recognition. Learn about real-world applications in various fields.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Computer Vision Features - Part 2 - Lecture 9

Explore advanced feature detection techniques including corner detection, HOG, and SIFT, focusing on their mathematical foundations and practical applications in computer vision.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Computer Vision: Edge Detection Techniques - Part 1 - Lecture 4

Explore edge detection techniques, including origins, types, and applications. Learn about intensity profiles, noise effects, smoothing solutions, and evaluation methods for effective edge detection.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Linear Algebra Basics for Computer Vision - Lecture 2

Explore essential linear algebra concepts including vectors, matrices, transformations, and SVD, with practical applications in computer vision and machine learning.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Introduction to Computer Vision - Lecture 1

Introduction to computer vision concepts, applications, and recent advancements. Explores visual perception, image types, object recognition, facial analysis, action detection, and video processing techniques.

• YouTube
• 49 minutes
• On-Demand
• Free Video

Computer Vision - Administrative Introduction - Fall 2020

Introduction to computer vision course covering topics, grading, expectations, and projects. Provides essential administrative information for students to succeed in the class.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Capsule Networks for Computer Vision – CVPR 2019 Tutorial

Explore capsule networks for computer vision, covering architecture, challenges, applications, and advancements in this cutting-edge deep learning approach.

• YouTube
• 2 hours 41 minutes
• On-Demand
• Free Video

Introduction to Capsule Networks for Computer Vision

Explore Capsule Networks for computer vision, covering sparse pattern recognition, viewpoint equivariance, object detection, and dynamic routing techniques.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Object Detection in Computer Vision - Lecture 21

Explore advanced object detection techniques, including precision-recall metrics, mean average precision, and multitask networks for computer vision applications.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Classification in Computer Vision - Part II - Lecture 19

Explore advanced classification techniques in computer vision, including SVMs, neural networks, and fully convolutional networks. Learn about activation functions, loss functions, and optimization for effective model training.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Classification in Computer Vision - Lecture 18

Explore classification in computer vision, covering features, linear classification, nearest neighbor, decision boundaries, and maximum margin classifiers. Gain insights into fundamental algorithms and problem-solving approaches.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video