Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a ...

Nvidia vice president of autonomous driving software Sarah Tariq relishes facing the challenges the future holds.

Digital systems are expected to navigate real-world environments, understand multimedia content, and make high-stakes ...

representing a notable advancement in robotic vision capabilities. Autonomous systems like drones, self-driving cars, and robots are becoming more common in our daily lives. However, they often ...

Chinese EV automaker Nio has developed its own chip set and SkyOS whole-vehicle operating system, making the latter “open ...

The use of autonomous ... to keep the vehicles moving. Researchers at Oak Ridge National Laboratory (ORNL) used machine learning and computer vision to design a system that can keep traffic ...

Conventional silicon architecture has taken computer vision a ... digital camera systems used in applications like self-driving cars and autonomous robots. “Computer vision systems use a huge amount ...

Advancements in artificial intelligence (AI) and computer vision ... autonomous systems capable of performing complex tasks. Autonomous robots are programmed with AI to recognize and learn from their ...

The swirl of activity around L4 and L5 vehicles ... Vision, radar and lidar DSPs at Cadence. “Applications like autonomous rail shuttles, track inspection cars, self-driving railway freight cars, ...

is the second in a series that puts Tesla's Autopilot system under the microscope. It links the cause of some crashes to Autopilot's overreliance on computer vision, which is basically a way of ...