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» Evaluating Algorithms for Concept Description
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141
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TMM
2010
231views Management» more  TMM 2010»
14 years 10 months ago
Real-Time Visual Concept Classification
As datasets grow increasingly large in content-based image and video retrieval, computational efficiency of concept classification is important. This paper reviews techniques to ac...
Jasper R. R. Uijlings, Arnold W. M. Smeulders, Rem...
137
Voted
APWEB
2006
Springer
15 years 7 months ago
Image Description Mining and Hierarchical Clustering on Data Records Using HR-Tree
Since we can hardly get semantics from the low-level features of the image, it is much more difficult to analyze the image than textual information on the Web. Traditionally, textu...
Congle Zhang, Sheng Huang, Gui-Rong Xue, Yong Yu
204
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ALDT
2011
Springer
262views Algorithms» more  ALDT 2011»
14 years 3 months ago
Learning Complex Concepts Using Crowdsourcing: A Bayesian Approach
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
111
Voted
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
15 years 8 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
ICASSP
2010
IEEE
15 years 3 months ago
Detecting local semantic concepts in environmental sounds using Markov model based clustering
Detecting the time of occurrence of an acoustic event (for instance, a cheer) embedded in a longer soundtrack is useful and important for applications such as search and retrieval...
Keansub Lee, Daniel P. W. Ellis, Alexander C. Loui