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» Learning Object Representations Using Sequential Patterns
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IJON
2008
116views more  IJON 2008»
13 years 7 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
CVPR
2005
IEEE
14 years 1 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
MICCAI
2002
Springer
14 years 8 months ago
RBF-Based Representation of Volumetric Data: Application in Visualization and Segmentation
A new scheme of data-driven segmentation is proposed, which is based on detection of object boundary, and volumetric pattern reconstruction as implicit function by using the detect...
Yoshitaka Masutani
ICCV
2007
IEEE
14 years 9 months ago
Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen
CVPR
2007
IEEE
14 years 9 months ago
Discovery of Collocation Patterns: from Visual Words to Visual Phrases
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...
Junsong Yuan, Ying Wu, Ming Yang