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» Virtual Training for Multi-View Object Class Recognition
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IJSI
2008
156views more  IJSI 2008»
15 years 1 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
CVPR
2007
IEEE
16 years 3 months ago
Using Segmentation to Verify Object Hypotheses
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Deva Ramanan
PRL
2007
166views more  PRL 2007»
15 years 1 months ago
Boosted Landmarks of Contextual Descriptors and Forest-ECOC: A novel framework to detect and classify objects in cluttered scene
In this paper, we present a novel methodology to detect and recognize objects in cluttered scenes by proposing boosted contextual descriptors of landmarks in a framework of multi-...
Sergio Escalera, Oriol Pujol, Petia Radeva
122
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ICCV
2007
IEEE
16 years 3 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
CVPR
2011
IEEE
14 years 10 months ago
Learning to Share Visual Appearance for Multiclass Object Detection
We present a hierarchical classification model that allows rare objects to borrow statistical strength from related objects that have many training examples. Unlike many of the e...
Ruslan Salakhutdinov, Antonio Torralba, Josh Tenen...