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» Learning Models for Object Recognition
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SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 4 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
SSPR
1998
Springer
15 years 6 months ago
Tracking of Rotating Objects
Abstract. A representation of a three-dimensional object is autonomously learned from a sequence of the rotating object. The representation consists of single views in form of grap...
Gabriele Peters, Christian Eckes, Christoph von de...
WWW
2005
ACM
16 years 2 months ago
Ontology-based learning content repurposing
This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way. Currently, t...
Katrien Verbert, Dragan Gasevic, Jelena Jovanovic,...
ROBOCUP
2007
Springer
162views Robotics» more  ROBOCUP 2007»
15 years 7 months ago
Adaptive Recognition of Color-Coded Objects in Indoor and Outdoor Environments
Abstract. To achieve robust color perception under varying light conditions in indoor and outdoor environments, we propose a three-step method consisting of adaptive camera paramet...
Yasutake Takahashi, Walter Nowak, Thomas Wisspeint...
CVPR
2006
IEEE
15 years 7 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...