13.3.8.2 Maximum Likelihood Estimation, Classification

Chapter Contents (Back)
Maximum Likelihood.

Haslett, J.[John],
Maximum likelihood discriminant analysis on the plane using a Markovian model of spatial context,
PR(18), No. 3-4, 1985, pp. 287-296.
WWW Version. 0309 BibRef
Earlier: PR(17), No. 6, 1984, pp. Page 677.
WWW Version. 0309 BibRef

Venkateswarlu, N.B., Raju, P.S.V.S.K.,
Three stage ML classifier,
PR(24), No. 11, 1991, pp. 1113-1116.
WWW Version. 0401fast version of the maximum likelihood classifier. BibRef

Venkateswarlu, N.B., Balaji, S., Raju, P.S.V.S.K., Boyle, R.D.,
Some further results of three stage ML classification applied to remotely sensed images,
PR(27), No. 10, October 1994, pp. 1379-1396.
WWW Version. 0401 BibRef

Brillault-O'Mahony, B., Ellis, T.J.,
A Maximum Likelihood Approach to Feature Segmentation,
PR(26), No. 5, May 1993, pp. 787-798.
WWW Version. BibRef 9305

Zhang, J., Modestino, J.W., Langan, D.A.,
Maximum-Likelihood Parameter Estimation for Unsupervised Stochastic Model-Based Image Segmentation,
IP(3), No. 4, July 1994, pp. 404-420.
WWW Version. See also Cluster Validation for Unsupervised Stochastic Model-Based Image Segmentation. BibRef 9407

Fessler, J.A., Hero, III, A.O.,
Penalized maximum-likelihood image reconstruction using space-alternating generalized EM algorithms,
IP(4), No. 10, October 1995, pp. 1417-1429.
WWW Version. 0402 BibRef

Li, T.F.[Tze Fen],
An efficient algorithm to find the MLE of prior probabilities of a mixture in pattern recognition,
PR(29), No. 2, February 1996, pp. 337-339.
WWW Version. 0401maximum likelihood estimation. BibRef

Chen, C.H., Tu, T.M.,
Computation Reduction of the Maximum-Likelihood Classifier Using the Winograd Identity,
PR(29), No. 7, July 1996, pp. 1213-1220.
WWW Version. 9607 BibRef

McLachlan, G.J., Peel, D., Whiten, W.J.,
Maximum likelihood clustering via normal mixture models,
SP:IC(8), No. 2, March 1996, pp. 105-111.
WWW Version. See also Bias associated with the discriminant analysis approach to the estimation of mixing proportions. BibRef 9603

McLachlan, G.J.[Geoff J.], Peel, D.,
Mixfit: An Algorithm for the Automatic Fitting and Testing of Normal Mixture Models,
ICPR98(Vol I: 553-557).
WWW Version. 9808 BibRef

Zhou, Z.Y., Leahy, R.M., Qi, J.Y.,
Approximate Maximum-Likelihood Hyperparameter Estimation for Gibbs-Priors,
IP(6), No. 6, June 1997, pp. 844-861.
WWW Version. 9705 BibRef

Zhou, Z.Y., Leahy, R.M.,
Approximate maximum likelihood hyperparameter estimation for Gibbs priors,
ICIP95(II: 284-287).
WWW Version. 9510 BibRef

Handley, J.C., Dougherty, E.R.,
Maximum-Likelihood-Estimation for the Two-Dimensional Discrete Boolean Random Set and Function Models Using Multidimensional Linear Samples,
GMIP(59), No. 4, July 1997, pp. 221-231. 9709 BibRef

Handley, J.C.[John C.], Dougherty, E.R.[Edward R.],
Maximum-likelihood estimation and optimal filtering in the nondirectional, one-dimensional binomial germ-grain model,
PR(32), No. 9, September 1999, pp. 1529-1541.
WWW Version. BibRef 9909

Vehtari, A.[Aki], Lampinen, J.[Jouko],
Bayesian MLP neural networks for image analysis,
PRL(21), No. 13-14, December 2000, pp. 1183-1191. 0011 BibRef
Earlier:
Bayesian Neural Networks for Image Analysis,
SCIA99(Neural Nets). BibRef

Lee, C., Choi, E.,
Bayes Error Evaluation of the Gaussian ML Classifier,
GeoRS(38), No. 3, May 2000, pp. 1471-1475.
IEEE Top Reference. 0006 BibRef

Raudys, A.[Aistis], Long, J.A.,
MLP Based Linear Feature Extraction for Nonlinearly Separable Data,
PAA(4), No. 4 2001, pp. 227-234.
HTML Version. 0202 BibRef

Raudys, A.[Aistis],
Accuracy of MLP Based Data Visualization Used in Oil Prices Forecasting Task,
CIAP05(761-769).
WWW Version. 0509 BibRef

Hayat, M.M., Abdullah, M.S., Joobeur, A., Saleh, B.E.A.,
Maximum-likelihood image estimation using photon-correlated beams,
IP(11), No. 8, August 2002, pp. 838-846.
WWW Version. 0209 BibRef

Hung, M.C.[Ming-Chih], Ridd, M.K.[Merrill K.],
A Subpixel Classifier for Urban Land-Cover Mapping Based on a Maximum-Likelihood Approach and Expert-System Rules,
PhEngRS(68), No. 11, November 2002, pp. 1173-1180. A supervised classifier based on a maximum-likelihood approach, TM image characteristics, the V-I-S model, and expert system rules, to estimate ground component composition of urban areas at the subpixel level.
WWW Version. 0304 BibRef

Xie, J., Tsui, H.T.,
Image segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED),
PRL(25), No. 10, 16 July 2004, pp. 1133-1141.
WWW Version. 0407 BibRef

Xie, J.[Jun], Tsui, H.T., Xia, D.[Deshen],
Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED),
ICPR02(I: 707-710).
WWW Version. 0211 BibRef

Meignen, S., Meignen, H.,
On the Modeling of Small Sample Distributions With Generalized Gaussian Density in a Maximum Likelihood Framework,
IP(15), No. 6, June 2006, pp. 1647-1652.
WWW Version. 0606Model distributions. BibRef

Pi, M.H.[Ming-Hong],
Improve maximum likelihood estimation for subband GGD parameters,
PRL(27), No. 14, 15 October 2006, pp. 1710-1713.
WWW Version. 0609Generalized Gaussian density; Moment estimator; Maximum likelihood estimator; Newton-Raphson iteration; Regula-Falsi iteration BibRef


Nestares, O., Fleet, D.J.,
Error-in-variables likelihood functions for motion estimation,
ICIP03(III: 77-80).
IEEE Abstract. IEEE Top Reference. 0312 BibRef

Nestares, O.[Oscar], Fleet, D.J.[David J.], Heeger, D.J.[David J.],
Likelihood Functions and Confidence Bounds for Total-Least-Squares Problems,
CVPR00(I: 523-530).
IEEE Abstract. IEEE Top Reference.
WWW Version. 0005 BibRef

Um, I.T., Ra, J.H., Kim, M.H.,
Comparison of Clustering Methods for MLP-based Speaker Verification,
ICPR00(Vol II: 475-478).
WWW Version.
HTML Version. 0009 BibRef

El Malek, J., Alimi, A.M., Tourki, R.,
Effect of the Feature Vector Size on the Generalization Error: The Case of MLPNN and RBFNN Classifiers,
ICPR00(Vol II: 630-633).
WWW Version.
HTML Version. 0009 BibRef

Gimel'Farb, G.[Georgy],
On the Maximum Likelihood Potential Estimates for Gibbs Random Field Image Models,
ICPR98(Vol II: 1598-1600).
WWW Version. 9808 BibRef

Grim, J.,
Maximum-Likelihood Design of Layered Neural Networks,
ICPR96(IV: 85-89).
WWW Version. 9608(Academy of Sciences, CZ) BibRef

Berrim, S., Lansiart, A., Moretti, J.L.,
Implementing of maximum likelihood in tomographical coded aperture,
ICIP96(II: 745-748).
WWW Version. 9610 BibRef

Sun, Y.[Yi],
Tracking and detection of moving point targets in noise image sequences by local maximum likelihood,
ICIP96(III: 799-802).
WWW Version. 9610 BibRef

Moghaddam, B., Pentland, A.,
A subspace method for maximum likelihood target detection,
ICIP95(III: 512-515).
WWW Version. 9510 BibRef

Meir, R.,
Empirical risk minimization versus maximum-likelihood estimation: A case study,
ICPR94(B:295-299).
WWW Version. 9410 BibRef

Endoh, T., Toriu, T., Tagawa, N.,
The maximum likelihood estimator is not 'optimal' on 3-D motion estimation from noisy optical flow,
ICIP94(II: 247-251).
WWW Version. 9411 BibRef

Tagawa, N., Toriu, T., Endoh, T.,
An objective function for 3-D motion estimation from optical flow with lower error variance than maximum likelihood estimator,
ICIP94(II: 252-256).
WWW Version. 9411 BibRef

Schultz, R.R., Stevenson, R.L., Lumsdaine, A.,
Maximum likelihood parameter estimation for non-Gaussian prior signal models,
ICIP94(II: 700-704).
WWW Version. 9411 BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Bayesian Networks, Bayes Nets .


Last update:Aug 27, 2008 at 19:16:50