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» Structural Learning of Activities from Sparse Datasets
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CVPR
2012
IEEE
11 years 11 months ago
Bridging the past, present and future: Modeling scene activities from event relationships and global rules
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
ICIP
2009
IEEE
13 years 6 months ago
Robust extraction of urinary stones from CT data using attribute filters
In medical imaging, anatomical and other structures such as urinary stones, are often extracted with the aid of active contour/surface models. Active surface-based methods have ro...
Georgios K. Ouzounis, Stilianos Giannakopoulos, Co...
PKDD
2010
Springer
183views Data Mining» more  PKDD 2010»
13 years 7 months ago
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
Zhao Xu, Kristian Kersting, Thorsten Joachims
BMCBI
2008
99views more  BMCBI 2008»
13 years 8 months ago
Binning sequences using very sparse labels within a metagenome
Background: In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the cu...
Chon-Kit Kenneth Chan, Arthur L. Hsu, Saman K. Hal...
CSL
2010
Springer
13 years 8 months ago
Active learning and semi-supervised learning for speech recognition: A unified framework using the global entropy reduction maxi
We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...