Lectures related to Activity recognition

Thermal Comfort Monitoring: Non-Intrusive Solutions

Presents a framework for non-intrusive thermal comfort monitoring using computer vision and machine learning techniques.

Deep Visual Recognition: Interpretability

Explores deep visual recognition, interpretability, CNN architectures, visual dictionaries, and attention mechanisms.

Fine-Grained Visual Categorization: Challenges and Solutions

Explores challenges and solutions in fine-grained visual categorization, focusing on computer vision and machine learning.

NFNets: Removing BatchNorm for High-Performance Image Recognition

Explores NFNets as an alternative to BatchNorm in ResNets, achieving high performance on ImageNet.

Deep Learning: No Free Lunch Theorem and Inductive Bias

Covers the No Free Lunch Theorem and the role of inductive bias in deep learning and reinforcement learning.

Image Recognition: Datasets and Algorithms

Explores a 2019 paper on image recognition, dataset challenges, biases, and the impact of large-scale datasets on deep learning models.

Faster Gaze Prediction: Dense Networks and Fisher Pruning

Explores the development of faster architectures for saliency prediction using deep networks and pruning methods.

MaxPooling as inductive bias for images

Explores how MaxPooling enforces an inductive bias towards local translation invariance in convolutional neural networks.

Topology: Polyhedral Products and Edge Detection

Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.

Deep Learning Fundamentals

Introduces the fundamentals of deep learning, covering neural networks, CNNs, special layers, weight initialization, data preprocessing, and regularization.

Modern Convolutional Networks and Image Recognition

Explores the evolution of deep convolutional networks and their impact on image recognition accuracy.

Transformer Architecture: The X Gomega

Delves into the Transformer architecture, self-attention, and training strategies for machine translation and image recognition.

Socially-aware Artificial Intelligence for Last-mile Mobility

Explores socially-aware AI for last-mile mobility, focusing on understanding social etiquettes, anticipating behaviors, and forecasting crowd movements.

Machine Learning Fundamentals Log in to Mediaspace to watch this video

Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.

AI and Ethics Log in to Mediaspace to watch this video

Delves into the potential and ethical challenges of AI technologies, emphasizing responsible research and diverse datasets.

Programming Project: Image Recognition Log in to Mediaspace to watch this video

Explains image recognition in LabVIEW, focusing on reading parameters and recognizing digits.

Transformers in Vision Log in to Mediaspace to watch this video

Explores Transformers in computer vision, focusing on 'Attention Is All You Need' architecture and its applications in visual tasks.

Visual Intelligence: Machines and Minds Log in to Mediaspace to watch this video

Explores the history and techniques of computer vision, covering image formation, transformation, dynamic perspectives, and 3D estimation cues.

Visual Intelligence: Machines and Minds Log in to Mediaspace to watch this video

Explores visual intelligence, image formation, computer vision, and representation understanding in machines and minds.

Computer Vision History Recap Log in to Mediaspace to watch this video

Offers a historical overview of computer vision, exploring key developments and influential figures in the field.