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» Comparing segmentations by applying randomization techniques
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SIGIR
2003
ACM
15 years 7 months ago
Table extraction using conditional random fields
The ability to find tables and extract information from them is a necessary component of data mining, question answering, and other information retrieval tasks. Documents often c...
David Pinto, Andrew McCallum, Xing Wei, W. Bruce C...
ICML
2005
IEEE
16 years 2 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
ICIP
2000
IEEE
16 years 3 months ago
Joint Space-Frequency Segmentation, Entropy Coding and the Compression of Ultrasound Images
Joint space-frequency segmentation is a relatively new image compression technique that finds the rate-distortion optimal representation of an image from a large set of possible s...
Ed Chiu, Jacques Vaisey, M. Stella Atkins
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 2 months ago
Assessing data mining results via swap randomization
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
109
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ICIAP
1999
ACM
15 years 6 months ago
Texture Segmentation by Frequency-Sensitive Elliptical Competitive Learning
In this paper a new learning algorithm is proposed with the purpose of texture segmentation. The algorithm is a competitive clustering scheme with two specific features: elliptic...
Steve De Backer, Paul Scheunders