Computer Architecture Courses

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

Edge Detection in Computer Vision - Part II - Lecture 7

Explore advanced edge detection techniques, including Canny algorithm and deep learning approaches, for improved computer vision applications in image processing and analysis.

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

Edge Detection in Computer Vision - Part I - Lecture 6

Comprehensive exploration of edge detection in computer vision, covering types, applications, algorithms, and evaluation methods. Includes real-world examples and practical insights for implementation.

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

Image Filtering in Computer Vision - Part II - Lecture 5

Explore advanced image filtering techniques, including derivative operations, Gaussian smoothing, and various filter types. Learn their applications and properties in computer vision.

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

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

Explore essential linear algebra concepts for computer vision, including matrix operations, determinants, and transformations, enhancing your understanding of image processing fundamentals.

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

Introduction to Computer Vision - Part II - Lecture 2

Explore computer vision fundamentals, deep learning applications, and advanced topics like object detection, segmentation, and action recognition in images and videos.

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