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» The Dark Side of Object Learning: Learning Objects
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CVPR
2004
IEEE
14 years 11 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
ICPR
2004
IEEE
14 years 10 months ago
Object Recognition Using Segmentation for Feature Detection
: A new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. We assume that each object can be characterized by a se...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
ICANN
2009
Springer
14 years 3 months ago
Selective Attention Improves Learning
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
Antti Yli-Krekola, Jaakko Särelä, Harri ...
OTM
2004
Springer
14 years 2 months ago
Domain Ontology as a Resource Providing Adaptivity in eLearning
Abstract. This paper presents a knowledge-based approach to eLearning, where the domain ontology plays central role as a resource structuring the learning content and supporting ï¬...
Galia Angelova, Ognian Kalaydjiev, Albena Strupcha...
ECCV
2010
Springer
14 years 2 months ago
Category Independent Object Proposals
We propose a category-independent method to produce a bag of regions and rank them, such that top-ranked regions are likely to be good segmentations of different objects. Our key ...