We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
In this paper we study various chain codes, which are representations of binary image contours, in terms of their ability to compress in the best way the contour information using...
Background: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for ...
Timothy Lu, Christine M. Costello, Peter J. P. Cro...