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ICASSP
2011
IEEE
14 years 10 months ago
Dictionary learning of convolved signals
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...
Daniele Barchiesi, Mark D. Plumbley
CVPR
2012
IEEE
13 years 9 months ago
Learning features on robotic surgical tools
Computer-aided surgical interventions in both manual and robotic procedures have been shown to improve patient outcomes and enhance the skills of the human physician. Tool trackin...
Austin Reiter, Peter K. Allen, Tao Zhao
ICCV
2009
IEEE
16 years 12 months ago
Constrained Clustering by Spectral Kernel Learning
Clustering performance can often be greatly improved by leveraging side information. In this paper, we consider constrained clustering with pairwise constraints, which specify s...
Zhenguo Li, Jianzhuang Liu
CVPR
2008
IEEE
16 years 9 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
ICIP
2004
IEEE
16 years 8 months ago
Automatically learning structural units in educational videos with the hierarchical hidden markov models
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui