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From Communities of Practice to Community Based Decision Making — Case Ericsson
Artificial General Intelligence and AI in Games
Cryptography Reading Group
Cybersecurity Breakfast Talks
Data Systems Group
DeIC offer Sep 2017
Former members of the department (partial list)
Jean Melo PhD
PhD Defense of Jean Melo
Remotely controlled drug delivery with chemical micro-robots.
State of Low-power Wireless Protocols for IoT
Talk Alan Mycroft 9 June 2017
Talk by Alexander Serebrenik on Aug 31, 2017
TALK by Rohit Gheyi on Aug 31, 2017
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Talk Søren Hauberg 28 Apr 2017
Diffeomorphisms for Dummies and Augmentations for Awesommies
, DTU Compute
Fri 28 Apr 2017 at 11:00-12:00
Jes Frellsen (part of ML Seminar Series)
Deep learning is making tremendous impact in computer vision and machine learning tasks where data is plentiful. However, those of us not working for a big data collection company often find that data is not as plentiful as needed. A common trick is to artificially increase the size of your data set by synthetically deforming the data, e.g. new images can be generated by rotating old ones. The difficult part is to find the right set of deformations to apply, which is a manual laborious task akin to feature engineering in classic computer vision. I'll present some techniques for automating these processes. To get there, we'll discuss links to image registration, infinite dimensional Lie groups, and deep neural networks.
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