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» Learning to Recognize Objects from Unseen Modalities
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ICPR
2006
IEEE
15 years 10 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
FGCN
2008
IEEE
175views Communications» more  FGCN 2008»
15 years 4 months ago
Environment Recognition Based on Human Actions Using Probability Networks
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
Hiroshi Miki, Atsuhiro Kojima, Koichi Kise
HIS
2007
14 years 11 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
AAAI
2004
14 years 11 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
CVPR
2006
IEEE
15 years 11 months ago
Identifying Color in Motion in Video Sensors
Identifying or matching the surface color of a moving object in surveillance video is critical for achieving reliable object-tracking and searching. Traditional color models provi...
Gang Wu, Amir Rahimi, Edward Y. Chang, Kingshy Goh...