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» Learning the Relative Importance of Features in Image Data
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ICRA
2002
IEEE
121views Robotics» more  ICRA 2002»
15 years 9 months ago
A Tale of Two Filters - On-Line Novelty Detection
Abstract— For mobile robots, as well as other learning systems, the ability to highlight unexpected features of their environment – novelty detection – is very useful. One pa...
Paul A. Crook, Stephen Marsland, Gillian Hayes, Ul...
SMI
2006
IEEE
144views Image Analysis» more  SMI 2006»
15 years 10 months ago
Robust Alignment of Multi-view Range Data to CAD Model
Surface matching is a common task in computer graphics and computer vision. In this paper, we introduce a novel algorithm that aligns scanned point-based surfaces to the related 3...
Xinju Li, Igor Guskov, Jacob Barhak
HICSS
2005
IEEE
130views Biometrics» more  HICSS 2005»
15 years 9 months ago
Knowledge Flow in Interdisciplinary Teams
Knowledge flow in interdisciplinary teams has become of particular interest as research and alliances cross traditional disciplinary boundaries, and as computing is applied in any...
Caroline Haythornthwaite
151
Voted
ECCV
2010
Springer
15 years 8 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
152
Voted
CVPR
2006
IEEE
16 years 6 months ago
A Simple Bayesian Framework for Content-Based Image Retrieval
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Katherine A. Heller, Zoubin Ghahramani