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» Learning a Classification Model for Segmentation
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ICIP
2003
IEEE
14 years 10 months ago
Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
X. Song, G. Fan
IJCV
2008
266views more  IJCV 2008»
13 years 9 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
NN
2006
Springer
13 years 9 months ago
Machine learning in soil classification
In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the cons...
Biswanath Bhattacharya, Dimitri P. Solomatine
CHI
2009
ACM
14 years 9 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
CVPR
2005
IEEE
14 years 11 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman