The Department of Engineering Science’s Seebibyte Project is holding a "Show and Tell" to introduce and demonstrate advanced machine learning methods that enable automated analysis of image and video data across research disciplines. This session will focus on work developed by Andrew Zisserman, Alison Noble, and Andrea Vedaldi.
In the Morning Session (11.00 to 13.00) we will demonstrate software developed by the Visual Geometry Group, and advise how it can immediately be applied to your own projects. The presentations will cover the following topics: 1) Counting; 2) Landmark Detection (Keypoint Detection); 3) Segmentation (Region Labelling); and 4) Text Spotting. Lunch will be provided (13.00-14.00).
In the Afternoon Session (14.00 to 16.00) there will be short one-to-one meetings to discuss in detail how the software might be developed for particular projects.
Venue: Department of Engineering Science (details on registration)
Pre-registration is required.
Further details and registration here: www.seebibyte.org/June14.html
Or contact Penny Farrar, Seebibyte Project Manager: email@example.com