Lectures related to Visual Intelligence: Embodied AI

Neural Networks: Two Layers Neural Network

Covers the basics of neural networks, focusing on the development from two layers neural networks to deep neural networks.

Neural Networks: Multilayer Perceptrons

Covers Multilayer Perceptrons, artificial neurons, activation functions, matrix notation, flexibility, regularization, regression, and classification tasks.

Deep Learning: Theory and Applications

Explores the mathematics of deep learning, neural networks, and their applications in computer vision tasks, addressing challenges and the need for robustness.

Deep Learning: Convolutional Neural Networks

Covers Convolutional Neural Networks, standard architectures, training techniques, and adversarial examples in deep learning.

Perception: Data-Driven Approaches

Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.

Deep Learning for Autonomous Vehicles: Learning

Explores learning in deep learning for autonomous vehicles, covering predictive models, RNN, ImageNet, and transfer learning.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

Neural Architectures for Embodied AI and Cognition Log in to Mediaspace to watch this video

Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.

Perceptual Robotics: Integrating Vision and Action Log in to Mediaspace to watch this video

Covers the integration of visual perception and robotic actions in embodied AI.

Machine Learning for Feature Extraction Log in to Mediaspace to watch this video

Explores machine learning for feature extraction, 3D vision, and neural networks in mobile robotics.

Transformers in Vision: Applications and Architectures Log in to Mediaspace to watch this video

Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.

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.

Transformers: Unifying Machine Learning Communities Log in to Mediaspace to watch this video

Covers the role of Transformers in unifying various machine learning fields.

Computer Vision: Historical Insights and Project Inspirations Log in to Mediaspace to watch this video

Explores the historical development of computer vision and inspires innovative project ideas.

Transformers in Robotics: Applications and Innovations Log in to Mediaspace to watch this video

Covers the use of transformers in robotics, focusing on embodied perception and innovative applications in humanoid locomotion and reinforcement learning.

Deep Learning: Principles and Applications Log in to Mediaspace to watch this video

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.

Neural Taskonomy and Historical Perspectives in Visual Intelligence Log in to Mediaspace to watch this video

Covers Neural Taskonomy, the evolution of neural networks, and historical perspectives in visual intelligence.

Edge Detection: Deep Learning Insights Log in to Mediaspace to watch this video

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Transformers in Vision Log in to Mediaspace to watch this video

Explores the evolution of visual intelligence models, focusing on Transformers and their applications in computer vision and natural language processing.

Computer Vision: Fundamentals and Applications Log in to Mediaspace to watch this video

Covers the fundamentals of computer vision, illusions, challenges, applications, and history.