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» A Conic Section Classifier and its Application to Image Data...
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CVPR
2006
IEEE
14 years 5 months ago
A Conic Section Classifier and its Application to Image Datasets
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
Arunava Banerjee, Santhosh Kodipaka, Baba C. Vemur...
CVPR
2008
IEEE
14 years 5 months ago
Large margin pursuit for a Conic Section classifier
Learning a discriminant becomes substantially more difficult when the datasets are high-dimensional and the available samples are few. This is often the case in computer vision an...
Santhosh Kodipaka, Arunava Banerjee, Baba C. Vemur...
ECCV
2010
Springer
13 years 5 months ago
Improving the Fisher Kernel for Large-Scale Image Classification
Abstract. The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the context of image classification the FK was s...
ECCV
2008
Springer
14 years 5 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
2009
IEEE
14 years 8 months ago
Weakly supervised discriminative localization and classification: a joint learning process
Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...