About Us
Find out more about our team and facilities.
Welcome to the Vision, Learning and Control (VLC) research group. We are a highly numerate team covering much of the central theory in Electronics, Electrical Engineering and Computer Science. We cover a rich spread of technological areas encompassing control, machine learning and computer vision with a sizeable number of academic staff, PhD researchers and postdocs.
Research
Research in VLC encompasses all aspects of Computer Vision, Machine Learning and Control.
Find Us
Scientists investigate machine learning sensors...
Researchers from the University of Southampton are using machine learning techniques to develop the next generation of wear sensing in machines such as planes and cars.
Read MoreCentre for Machine Intelligence launched to...
Computer science experts discussed the key challenges surrounding emerging AI and blockchain technologies at the Centre for Machine Intelligence launch
Read MoreYoung university innovators unveil future...
Pioneering research, including an AI-powered video analytics platform, features at the 2018 Consumer Electronics Show in Las Vegas
Read MoreRecent VLC publications
Generalized norm optimal iterative learning control: constraint handling - Yiyang Chen, Bing Chu and Christopher T. Freeman
Type: Article
| 2017
| Item availability restricted.
Point-to-point iterative learning control with optimal tracking time allocation - Yiyang Chen, Bing Chu and Christopher T. Freeman
Type: Conference or Workshop Item
| 2015
| IEEE
| Item not available on this server.
A structured light approach to imaging ancient Near Eastern cylinder seals: how efficient 3D imaging may facilitate corpuswide research - Jacob Dahl, Jonathon Hare, Kate Kelley, Kirk Martinez and David Young
Type: Book Section
| 2018
| Archaeopress / British Archaeological Reports
How biased is your NLG evaluation? - Pavlos Vougiouklis, Eddy Maddalena, Jonathon Hare and Elena Simperl
Type: Conference or Workshop Item
| 2018
| Item not available on this server.
Neural Wikipedian: generating textual summaries from knowledge base triples - Pavlos Vougiouklis, Hady Elsahar, Lucie-Aimée Kaffee, Christophe Gravier, Frederique Laforest, Jonathon Hare and Elena Simperl
Type: Article
| 2018