The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
: This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propos...
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
This paper proposes a novel approach to motion capture
from multiple, synchronized video streams, specifically
aimed at recording dense and accurate models of the structure
and ...
Yasutaka Furukawa (University of Washington), Jean...
Consumer digital cameras use tone-mapping to produce compact, narrow-gamut images that are nonetheless visually pleasing. In doing so, they discard or distort substantial radiomet...
Ying Xiong, Kate Saenko, Trevor Darrell, Todd Zick...