Eclipse SDV Blueprints - Introduction to Software Defined Vehicle Solutions
Discover how Eclipse SDV Blueprints brings software-defined vehicle concepts to life through practical implementations, featuring data sharing, autonomous racing, and fleet management solutions.
Deep Learning Models for Autonomous Driving
Discover the latest autonomous driving deep learning models and innovations from Silicon Valley, featuring insights from a former Tesla Autopilot R&D expert and current Phantom AI CEO.
AI for Autonomous Mobile Robots - Computer Vision and Navigation Systems
Explore how AI and computer vision enable autonomous mobile robots to navigate safely alongside humans in logistics, focusing on deep learning, mapping, and advanced navigation algorithms.
Risk - The Toughest Barrier to Autonomous Cars
Explore the unexpected challenges in commercializing self-driving technology, focusing on mindset and legal hurdles rather than technical aspects.
Efficient 3D Perception for Autonomous Vehicles
Explore efficient 3D perception techniques for autonomous vehicles, including multi-sensor fusion, accelerated view transformation, and optimized backbones for real-time performance on edge devices.
Integrating Julia for Perception Tasks in Autonomous Driving
Explore Julia's potential in autonomous driving perception tasks, from LIDAR processing to ML algorithm development and integration in real vehicles.
Improving Developer Velocity in Safety Critical Applications
Maximize developer velocity while meeting quality and safety standards for autonomous truck control. Learn Aurora's strategies for efficient code changes and quality assurance.
How to Create ML Models That Teach Themselves - Unsupervised Learning in Self-Driving Cars
Explore self-driving car technology and unsupervised ML models with Helm.ai. Learn about deep teaching, real-world applications, and future enhancements in autonomous vehicle development.
Introduction to Deep Learning: Deep Learning Success Stories - Lecture 3
Explore deep learning success stories and their impact across various fields, gaining insights from Prof. A.N. Rajagopalan of IIT Madras.
From General AI to the Edge: Navigating the Future of Technology
Explore AI's evolution from broad principles to edge applications, examining its impact across industries and future trends while addressing ethical implications and technological challenges.
The Rise of Neural Priors
Explore neural priors as a solution to AI challenges, including data scarcity and bias. Learn about their applications in augmented reality, autonomous driving, and signal recovery.
Machines Behaving Badly: The Morality of AI
Explore ethical considerations and unexpected consequences of AI, including racism in AI assistants, robot rights, self-driving car accidents, and facial recognition limitations.
Spatio-Temporal Perception Logic for Verification of Perceptual Systems - Part 1
Explore spatio-temporal perception logic for verifying perceptual systems in autonomous vehicles and other safety-critical applications.
Spatio-Temporal Perception Logic for Perceptual Systems Verification - Part 2
Explore spatio-temporal perception logic for verifying perceptual systems in autonomous vehicles, building on Part 1's foundations.
Spatio-Temporal Perception Logic for Perceptual Systems Verification - Part 3
Explore spatio-temporal perception logic for verifying perceptual systems in autonomous vehicles, building on previous parts of the series.
Innovations in STEM: Racing Towards a Safer Future
Exploring technological advancements in autonomous driving and micro-mobility to enhance road safety. From racetracks to urban planning, innovations in STEM are shaping a smarter, safer future for transportation.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.
Automated Driving - Are We Taking the Human Factors Out of the Loop?
Explores the impact of automated driving on human factors, discussing efficiency gains, risks, levels of automation, and challenges in human-machine interaction for autonomous vehicles.
Self-Driving Cars
Explore the future of autonomous vehicles and their impact on energy consumption, lifestyle, and the Internet of Things in this insightful presentation by a distinguished engineering professor.
Cost-Effective Simulation-Based Test Selection in Self-Driving Cars SW
Explore cost-effective simulation-based testing for self-driving cars using SDC-Scissor, a machine learning framework to enhance safety and reduce testing costs.
Deep Learning in Computer Vision
Explore deep learning in computer vision, from basic concepts to advanced architectures. Learn to design networks that understand images, with practical examples and expert insights.