Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...
The growing potential of artificial intelligence (AI) and machine learning (ML) in embedded systems is driving new application solutions and products, but developing AI-based systems can be ...
March 31, 2005-- At SAE World Congress -11th April, Axeon and Infineon will launch their embedded machine learning system based on Axeon’s Vindax technology integrated with the Infineon Powertrain ...
Qeexo spun out of Carnegie Mellon University, has for a long time developed multi-touch technology for handset manufacturers which does ML on the device level. It has applied this approach to a new ...
AZoSensors on MSN
Low-power sensor node brings machine learning to the edge of environmental monitoring
A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time ...
Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results