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» Object correspondence as a machine learning problem
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AAAI
2004
15 years 1 months ago
On the Integration of Grounding Language and Learning Objects
This paper presents a multimodal learning system that can ground spoken names of objects in their physical referents and learn to recognize those objects simultaneously from natur...
Chen Yu, Dana H. Ballard
ECCV
2008
Springer
16 years 1 months ago
Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abhinav Gupta, Larry S. Davis
ICML
2005
IEEE
16 years 15 days ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ICCV
2007
IEEE
15 years 6 months ago
Support Kernel Machines for Object Recognition
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
Ankita Kumar, Cristian Sminchisescu
ICALT
2006
IEEE
15 years 5 months ago
Adaptive Learning Objects Sequencing for Competence-Based Learning
Lifelong learning refers to the activities people perform throughout their life to improve their competence in a particular field. Although adaptive educational hypermedia systems...
Pythagoras Karampiperis, Demetrios G. Sampson