Computer Architecture Courses

Advanced Computer Vision - Spring 2021

Dive into adversarial machine learning, explainable AI, and robust neural network architectures through cutting-edge research papers and advanced computer vision techniques.

• YouTube
• 12 hours 40 minutes
• Self-Paced
• Free Video

Computer Vision - Fall 2020

Master computer vision fundamentals from linear algebra to advanced neural networks, covering filtering, edge detection, CNNs, PyTorch, object detection, and segmentation techniques.

• YouTube
• 1 day 4 hours 50 minutes
• Self-Paced
• Free Video

Computer Vision

Master computer vision fundamentals from filtering and edge detection to SIFT, optical flow, camera calibration, and facial recognition through comprehensive lectures.

• YouTube
• 19 hours 7 minutes
• Self-Paced
• Free Video

Computer Vision Video Lectures 2012

Master computer vision fundamentals through comprehensive lectures covering filtering, edge detection, SIFT, optical flow, face recognition, and stereo vision techniques.

• YouTube
• 19 hours 28 minutes
• Self-Paced
• Free Video

CAP6412 - Advanced Computer Vision - Lecture 24: Project Presentations

Students present their projects, showcasing innovative approaches in computer vision and AI. Topics include object detection, video analysis, and visual question answering, highlighting challenges and novel solutions.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

Computer Vision: Tokens and Cross-View Fusion - Lecture 22

Explore tokens, cross-view fusion, and attention in computer vision, examining experimental results and innovations in multi-view learning techniques.

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

Computer Vision Architecture Evolution: ConvNets to Transformers - Lecture 21

Explore the evolution of vision architectures, comparing SWIN and CNNs, and learn about modernizing ConvNets with macro and micro design changes for improved performance.

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

Computer Vision - Adversarial Attacks and Deepfool Algorithm - Lecture 1

Explore DeepFool algorithm for generating adversarial examples in deep neural networks, covering linearization, multiclass classification, and experimental results.

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

Object Detection in Computer Vision - Lecture 22

Explore advanced object detection techniques in computer vision, including R-CNN, Fast R-CNN, and Faster R-CNN. Learn about training processes, region proposals, and improvements in detection algorithms.

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

Features in Computer Vision - Lecture 14

Explore feature types, uses, and characteristics in computer vision, including matching, structure from motion, and panorama stitching. Learn about interest points and corner detection for keypoint applications.

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

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

Explore neural network training techniques, including gradient descent, loss functions, and backpropagation, for effective computer vision model optimization and performance improvement.

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

Introduction to Neural Networks for Computer Vision - Part I

Introduction to neural networks for computer vision, covering key concepts like pixel representation, feature extraction, and image classification. Explores biological inspiration and computational implementation of neural activation functions.

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