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» Graph model selection using maximum likelihood
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ICIP
2008
IEEE
14 years 1 months ago
MAP-MRF approach for binarization of degraded document image
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probabil...
Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
ICASSP
2010
IEEE
13 years 7 months ago
Word confidence calibration using a maximum entropy model with constraints on confidence and word distributions
It is widely known that the quality of confidence measure is critical for speech applications. In this paper, we present our recent work on improving word confidence scores by cal...
Dong Yu, Shizhen Wang, Jinyu Li, Li Deng
ICMCS
2005
IEEE
123views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Hidden Markov Model Based Weighted Likelihood Discriminant for Minimum Error Shape Classification
The goal of this communication is to present a weighted likelihood discriminant for minimum error shape classification. Different from traditional Maximum Likelihood (ML) methods...
Ninad Thakoor, Sungyong Jung, Jean Gao
ICASSP
2008
IEEE
14 years 1 months ago
Maximum entropy relaxation for multiscale graphical model selection
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
TSP
2008
132views more  TSP 2008»
13 years 6 months ago
On Doubly Selective Channel Estimation Using Superimposed Training and Discrete Prolate Spheroidal Sequences
Abstract--Channel estimation and data detection for frequencyselective time-varying channels are considered using superimposed training. We employ a discrete prolate spheroidal bas...
Shuangchi He, Jitendra K. Tugnait