Efficient Deep Learning Hardware for Robotics and Autonomous Systems
Lead Participant:
MYRTLE SOFTWARE LIMITED
Abstract
There is a wide consensus that deep learning algorithms are key to the future of smart autonomous machines and robots. This project aims to automate the production of low power, lightweight hardware implementing these algorithms so that RAS applications become a reality.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| MYRTLE SOFTWARE LIMITED | £98,799 | £ 69,159 |
People |
ORCID iD |
| Peter Baldwin (Project Manager) |