A unified perspective and new results on RHT computing, mixture based learning, and multi-learner based problem solving

On one hand, multiple object detection approaches of Hough transform (HT) type and randomized HT type have been extended into an evidence accumulation featured general framework for problem solving, with five key mechanisms elaborated and several extensions of HT and RHT presented. On the other hand...

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Veröffentlicht in:	Pattern recognition Jg. 40; H. 8; S. 2129 - 2153
1. Verfasser:	Xu, Lei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.08.2007
Schlagworte:	Automatic model selection Bayesian Ying–Yang learning Elliptic RPCL Evidence combination Hough transform Local subspaces Mixture of experts Multi-sets modelling Object detection RBF nets Rival penalized competitive learning (RPCL) Multi-sets modelling Evidence combination Mixture of experts Bayesian Ying–Yang learning RBF nets Automatic model selection Object detection Elliptic RPCL Local subspaces Hough transform Rival penalized competitive learning (RPCL)
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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