Computer Architecture Courses

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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video

Introduction to Computer Vision - Part I - Lecture 1

Explore computer vision fundamentals, from image processing to deep learning applications. Covers perception, image types, and real-world uses in retail and autonomous vehicles.

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

Computer Vision - Administrative and Course Overview - Lecture 1

Introduction to graduate-level computer vision, covering mathematical foundations, deep learning applications, and advanced topics like object detection and image segmentation.

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

From Saliency to Camouflage Analysis in Computer Vision

Explore visual saliency and camouflage analysis in computer vision, covering FCN-based methods, semantic extraction, and applications. Learn about challenges and future directions in this field.

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

Computer Vision: Classification Techniques - Neural Networks and CNN Architecture - Lecture 12

Explore machine learning frameworks, neural networks, and CNN architecture, focusing on AlexNet and fully convolutional networks. Learn about activation functions and network composition.

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

Computer Vision Classification Techniques - Lecture 11

Explore Support Vector Machines (SVM) for classification, covering maximal-margin classifiers, non-separable cases, and nonlinear SVMs. Learn advantages and disadvantages of linear and nonlinear decision surfaces.

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

Computer Vision: Classification and Object Recognition - Lecture 11

Explore computer vision classification techniques, including object recognition, image classification, and machine learning frameworks. Learn about nearest neighbor and linear classifiers.

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

Autoencoder Architecture and Applications - Lecture 10

Explore autoencoders: architecture, comparison, applications in image retrieval, denoising, and anomaly detection. Gain insights into this powerful neural network technique.

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