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IJCAI
2007
15 years 6 months ago
Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition
Most existing sketch understanding systems require a closed domain to achieve recognition. This paper describes an incremental learning technique for opendomain recognition. Our s...
Andrew M. Lovett, Morteza Dehghani, Kenneth D. For...
AAAI
2004
15 years 6 months ago
Learning and Inferring Transportation Routines
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Lin Liao, Dieter Fox, Henry A. Kautz
AIR
2006
107views more  AIR 2006»
15 years 4 months ago
Just enough learning (of association rules): the TAR2 "Treatment" learner
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...
Tim Menzies, Ying Hu
MICCAI
2010
Springer
15 years 3 months ago
Incremental Shape Statistics Learning for Prostate Tracking in TRUS
Abstract. Automatic delineation of the prostate boundary in transrectal ultrasound (TRUS) can play a key role in image-guided prostate intervention. However, it is a very challengi...
Pingkun Yan, Jochen Kruecker
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 3 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara