Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.
Explores the significance of innovation in research, innovation, and business, emphasizing the multiplier effect of innovation and the future of disruptive technologies.
Explores uncertainty quantification and label error detection in deep learning for semantic segmentation, focusing on challenges and methods for error detection.
Presents an all-analog photoelectronic chip for high-speed vision tasks, addressing challenges in classical computation and proposing a hybrid optical-electrical framework.
Explores the dynamics and impact of autonomous vehicles, discussing their advantages, controversies, challenges, and integration considerations for future transport systems.
Explores safe automation challenges for intelligent systems, focusing on self-driving cars and proposing solutions based on system dynamics and filters.
