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» The Dark Side of Object Learning: Learning Objects
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SAC
2005
ACM
14 years 2 months ago
Rearranging data objects for efficient and stable clustering
When a partitional structure is derived from a data set using a data mining algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of...
Gyesung Lee, Xindong Wu, Jinho Chon
ICDAR
2011
IEEE
12 years 8 months ago
Objective Function Design for MCE-Based Combination of On-line and Off-line Character Recognizers for On-line Handwritten Japane
—This paper describes effective object function design for combining on-line and off-line character recognizers for on-line handwritten Japanese text recognition. We combine on-l...
Bilan Zhu, Jinfeng Gao, Masaki Nakagawa
CLOR
2006
14 years 25 days ago
Object Recognition in the Geometric Era: A Retrospective
Recent advances in object recognition have emphasized the integration of intensity-derived features such as affine patches with associated geometric constraints leading to impressi...
Joseph L. Mundy
ECOOPW
2000
Springer
14 years 1 months ago
Tools and Environments for Understanding Object-Oriented Concepts
The objective of this workshop was to discuss current tools and environments for learning object-oriented concepts and to share ideas and experiences about the usage of computer su...
Isabel Michiels, Alejandro Fernández, J&uum...
CVPR
2007
IEEE
14 years 11 months ago
Discriminant Additive Tangent Spaces for Object Recognition
Pattern variation is a major factor that affects the performance of recognition systems. In this paper, a novel manifold tangent modeling method called Discriminant Additive Tange...
Liang Xiong, Jianguo Li, Changshui Zhang