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» Learning from Multiple Sources of Inaccurate Data
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CVPR
2003
IEEE
14 years 9 months ago
Using Multiple Cues for Hand Tracking and Model Refinement
We present a model based approach to the integration of multiple cues for tracking high degree of freedom articulated motions and model refinement. We then apply it to the problem...
Shan Lu, Dimitris N. Metaxas, Dimitris Samaras, Jo...
ICASSP
2011
IEEE
12 years 11 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
ECCV
2010
Springer
13 years 12 months ago
Learning to Recognize Objects from Unseen Modalities
Abstract. In this paper we investigate the problem of exploiting multiple sources of information for object recognition tasks when additional modalities that are not present in the...
ICML
2004
IEEE
14 years 8 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
WWW
2011
ACM
13 years 2 months ago
Semi-supervised truth discovery
Accessing online information from various data sources has become a necessary part of our everyday life. Unfortunately such information is not always trustworthy, as different sou...
Xiaoxin Yin, Wenzhao Tan