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» The Dark Side of Object Learning: Learning Objects
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KDD
2012
ACM
247views Data Mining» more  KDD 2012»
11 years 11 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...
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
13 years 7 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
14 years 2 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
DEXAW
2005
IEEE
159views Database» more  DEXAW 2005»
14 years 2 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....
CVPR
2011
IEEE
13 years 5 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