With more than 1,200 attendees and over 90 presenters, the 2017 Embedded Vision Summit made one thing clear: I am not the only one who thinks that energy-efficient processors and simple-to-use software toolkits to utilize the available horse-power are critical for embedded vision. Jeff Bier made a compelling argument that cost and power consumption of vision computing will decrease by about 1000x over the next 3 years. He mentioned techniques like reducing data types and using software tools and frameworks to achieve significant improvements in resource usage and efficiency.
Read the full article on Embedded Vision Alliance Journal
You might also like
More from Imaging & vision
Transformer Models and NPU IP Co-Optimized for the Edge
Transformers are taking the AI world by storm, as evidenced by super-intelligent chatbots and search queries, as well as image …
What is AI Anomaly Detection and Why it needs Explainable AI (XAI)?
Anomaly detection is the process of identifying when something deviates from the usual and expected. If an anomaly can be …
CEVA & CERN: Where Edge AI and Particle Physics Intersect
In our day to day lives, technology driven experiences fall into different categories in terms of how much we understand …