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» A Boosting Approach to Multiple Instance Learning
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CVPR
2008
IEEE
14 years 9 months ago
Discovering class specific composite features through discriminative sampling with Swendsen-Wang Cut
This paper proposes a novel approach to discover a set of class specific "composite features" as the feature pool for the detection and classification of complex objects...
Feng Han, Ying Shan, Harpreet S. Sawhney, Rakesh K...
IJSR
2010
181views more  IJSR 2010»
13 years 6 months ago
Multi-Part People Detection Using 2D Range Data
People detection is a key capacity for robotics systems that have to interact with humans. This paper addresses the problem of detecting people using multiple layers of 2D laser ra...
Óscar Martínez Mozos, Ryo Kurazume, ...
DAGM
2010
Springer
13 years 8 months ago
On-Line Multi-view Forests for Tracking
Abstract. A successful approach to tracking is to on-line learn discriminative classifiers for the target objects. Although these trackingby-detection approaches are usually fast a...
Christian Leistner, Martin Godec, Amir Saffari, Ho...
SIGMOD
2008
ACM
131views Database» more  SIGMOD 2008»
14 years 7 months ago
Discovering topical structures of databases
The increasing complexity of enterprise databases and the prevalent lack of documentation incur significant cost in both understanding and integrating the databases. Existing solu...
Wensheng Wu, Berthold Reinwald, Yannis Sismanis, R...
AUSAI
2004
Springer
14 years 1 months ago
A Learning-Based Algorithm Selection Meta-reasoner for the Real-Time MPE Problem
Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
Haipeng Guo, William H. Hsu