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» A Framework for Machine Learning with Ambiguous Objects
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ICCV
2007
IEEE
14 years 1 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
ICALT
2007
IEEE
14 years 1 months ago
An Ontology-Based Framework for Authoring Assisted by Recommendation
In this paper, we propose the use of Semantic Web technologies to bridge the gap between authoring systems and authors. The core part of our solution is the ontology-based framewo...
Sasa Nesic, Dragan Gasevic, Mehdi Jazayeri
WWW
2008
ACM
14 years 8 months ago
A unified framework for name disambiguation
Name ambiguity problem has been a challenging issue for a long history. In this paper, we intend to make a thorough investigation of the whole problem. Specifically, we formalize ...
Jie Tang, Jing Zhang, Duo Zhang, Juanzi Li
ECCV
2008
Springer
14 years 9 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
ICCV
2005
IEEE
14 years 1 months ago
Object Detection in Aerial Imagery Based on Enhanced Semi-Supervised Learning
Object detection in aerial imagery has been well studied in computer vision for years. However, given the complexity of large variations of the appearance of the object and the ba...
Jian Yao, Zhongfei (Mark) Zhang