1 option
Graphical Networks and Motion Detection Electrical and Computer Engineering Department, University o.
- Format:
- Book
- Conference/Event
- Author/Creator:
- Hoxie, David J., author.
- Conference Name:
- 2024 NDIA Michigan Chapter Ground Vehicle Systems Engineering and Technology Symposium (2024-08-13 : Novi, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2024
- Summary:
- This works seeks to address fundamental research questions regarding the perception of autonomous vehicles. Most critical to the system is that the system be able to classify, predict and interpret spatial and temporal data. Further, this must be done on a time scale relevant to at least twice the speed of operational speeds of a vehicles to be able to successfully navigate potential head on collisions with other vehicles. Traditional tech requires a rethink, and that's to use ESN and RC type compute systems as they offer a much more efficient means of processing, training and adaptability over conventional networks. Further, a subset of these systems, graphical networks, work by embedding high dimensional information into a latent space for memorization, retrieval and other things. This ability makes graph nets a prime candidate. We demonstrate the first steps in a deployable graphical network for unmanned vehicles
- Notes:
- Vendor supplied data
- Publisher Number:
- 2024-01-4066
- Access Restriction:
- Restricted for use by site license
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.