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» The Dark Side of Object Learning: Learning Objects
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150
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KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 3 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
109
Voted
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
14 years 11 months ago
Searching for objects: Combining multiple cues to object locations using a maximum entropy model
— In this paper, we consider the problem of how background knowledge about usual object arrangements can be utilized by a mobile robot to more efficiently find an object in an ...
Dominik Joho, Wolfram Burgard
CVPR
2010
IEEE
15 years 6 months ago
Many-to-one Contour Matching for Describing and Discriminating Object Shape
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Praveen Srinivasan, Qihui Zhu, Jianbo Shi
70
Voted
DEXAW
2005
IEEE
159views Database» more  DEXAW 2005»
15 years 6 months ago
A Self-Healing Approach for Object-Oriented Applications
In this paper, we present our approach and architecture for fault diagnosis and self-healing of interpreted objectoriented applications. By combining aspect-oriented programming, ...
A. Reza Haydarlou, Benno J. Overeinder, Frances M....
114
Voted
CVPR
2011
IEEE
14 years 8 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman