Introduction to Neural Networks - Part II - Lecture 8
Explore neural network fundamentals, including activation functions, multi-class classification, and multi-layer perceptrons. Learn about their implementation and performance on image datasets like MNIST.
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.
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.
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.
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.
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.
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.
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.
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.
Evaluating Neural Network Robustness - Targeted Attacks and Defenses
Explore neural network robustness evaluation, including targeted attacks, metrics, and defense strategies. Learn about FGS, SMA, and new approaches for assessing and improving AI system security.
CAP6412 - Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Explore skip connections in ResNets, their impact on adversarial examples, and implications for model robustness and transferability in deep learning.
Imagen: Text-to-Image Generation Using Diffusion Models - Lecture 9
Explore Imagen, a text-to-image diffusion model, covering its architecture, efficiency improvements, and key techniques like thresholding and upsampling.
Introduction to Artificial Intelligence - Lecture 1
Comprehensive overview of course structure, objectives, and policies, with insights into AI topics like GPT and image generation.
Spatio-Temporal Learning from Limited Labels for Video Action Detection
Explore spatio-temporal learning techniques for video action detection with limited labels, focusing on semi-supervised methods and temporal coherence for improved performance.
Geo-localization Framework for Real-world Scenarios - Defense Presentation
Explore advanced geo-localization techniques using vision transformers and novel loss functions for improved accuracy in real-world scenarios, with a focus on bridging domain gaps.
Visual Question Answering: Grounded Systems and Transformer Capsules
Learn about Grounded Visual Question Answering systems, their limitations, and innovative approaches using Transformers with Capsules for improved performance in image-text understanding tasks.
Video Action Understanding - Action Classification, Temporal Localization and Detection
Explore video action understanding techniques, including classification, temporal localization, and detection methods for analyzing and interpreting human actions in video content.
Intro to Digital Image Processing Lectures, Spring 2015
Comprehensive exploration of digital image processing techniques, from fundamentals to advanced topics. Covers acquisition, manipulation, analysis, and applications of digital images across various domains.
Computer Vision for Visual Effects Lectures Spring 2014
The lectures accompany the textbook Computer Vision for Visual Effects, published by Cambridge University Press in Fall 2012.
Image Classification with ml5.js - MobileNet and Custom Models
Dive into image classification using ml5.js 1.0 in this comprehensive 32-minute video tutorial by Coding Train. Learn to implement both the default MobileNet model and train your own classifier using transfer learning and Teachable Machine. Explore the f…
Podman AI Lab: Building AI Applications with Local LLMs
Explore the features of Podman AI Lab, an extension of Podman Desktop, in this 29-minute conference talk from Devoxx. Discover sample AI applications (recipes) from the built-in catalog, including chatbots, audio-to-text conversion, and object detection.…