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CIVR
2006
Springer
219views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
CIVR
2006
Springer
139views Image Analysis» more  CIVR 2006»
13 years 11 months ago
NPIC: Hierarchical Synthetic Image Classification Using Image Search and Generic Features
We introduce NPIC, an image classification system that focuses on synthetic (e.g., non-photographic) images. We use class-specific keywords in an image search engine to create a no...
Fei Wang, Min-Yen Kan
ECCV
2010
Springer
14 years 14 hour 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...
KES
2005
Springer
14 years 1 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
ADMA
2006
Springer
167views Data Mining» more  ADMA 2006»
14 years 1 months ago
A Correlation Approach for Automatic Image Annotation
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
David R. Hardoon, Craig Saunders, Sándor Sz...