A Novel Gauss-Markov Random Field Approach for Regularization of Diffusion Tensor Maps

Computer Aided Systems Theory - EUROCAST 2003 - Lecture Notes in Computer Science ◽

10.1007/978-3-540-45210-2_46 ◽

2003 ◽

pp. 506-517 ◽

Cited By ~ 9

Author(s):

Marcos Martín-Fernández ◽

Raul San Josá-Estépar ◽

Carl-Fredrik Westin ◽

Carlos Alberola-López

Keyword(s):

Random Field ◽

Markov Random Field ◽

Diffusion Tensor ◽

Field Approach ◽

Markov Random

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Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach

Lecture Notes in Computer Science - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003 ◽

10.1007/978-3-540-39903-2_12 ◽

2003 ◽

pp. 92-100 ◽

Cited By ~ 3

Author(s):

Marcos Martín-Fernández ◽

Carlos Alberola-López ◽

Juan Ruiz-Alzola ◽

Carl-Fredrik Westin

Keyword(s):

Random Field ◽

Markov Random Field ◽

Diffusion Tensor ◽

Field Approach ◽

Gaussian Markov Random Field ◽

Markov Random ◽

Non Gaussian

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Reconstruction for distributed video coding: a Markov random field approach with context-adaptive smoothness prior

10.1117/12.863504 ◽

2010 ◽

Cited By ~ 1

Author(s):

Yongsheng Zhang ◽

Hongkai Xiong ◽

Zhihai He ◽

Songyu Yu

Keyword(s):

Video Coding ◽

Random Field ◽

Markov Random Field ◽

Distributed Video Coding ◽

Field Approach ◽

Markov Random

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A Finite Markov Random Field approach to fast edge-preserving image recovery

Image and Vision Computing ◽

10.1016/j.imavis.2006.05.021 ◽

2007 ◽

Vol 25 (6) ◽

pp. 792-804 ◽

Cited By ~ 11

Author(s):

Michele Ceccarelli

Keyword(s):

Random Field ◽

Markov Random Field ◽

Image Recovery ◽

Edge Preserving ◽

Field Approach ◽

Markov Random

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Interactive Image Segmentation using Improved Adaptive Markov Random Field Approach

Indian Journal of Science and Technology ◽

10.17485/ijst/2017/v10i6/94636 ◽

2017 ◽

Vol 10 (6) ◽

pp. 1-9

Author(s):

G. S. Gowri ◽

P. Ponmuthuramalingam ◽

◽

Keyword(s):

Image Segmentation ◽

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Interactive Image Segmentation ◽

Markov Random

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A Markov Random Field Approach to Edge Detection

MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference ◽

10.1109/melcon.2006.1653143 ◽

2006 ◽

Cited By ~ 2

Author(s):

L.J. Tardon ◽

I. Barbancho ◽

F. Marquez

Keyword(s):

Edge Detection ◽

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Markov Random

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A Markov random field approach to microarray image gridding

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. ◽

10.1109/icpr.2004.1334588 ◽

2004 ◽

Cited By ~ 16

Author(s):

G. Antoniol ◽

M. Ceccarelli

Keyword(s):

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Microarray Image ◽

Markov Random

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Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

IEEE Transactions on Image Processing ◽

10.1109/tip.2016.2622401 ◽

2017 ◽

Vol 26 (1) ◽

pp. 426-438 ◽

Cited By ~ 11

Author(s):

Peng Chen ◽

James D. B. Nelson ◽

Jean-Yves Tourneret

Keyword(s):

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Hyperspectral Unmixing ◽

Markov Random

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A latent discrete Markov random field approach to identifying and classifying historical forest communities based on spatial multivariate tree species counts

The Annals of Applied Statistics ◽

10.1214/19-aoas1259 ◽

2019 ◽

Vol 13 (4) ◽

pp. 2312-2340

Author(s):

Stephen Berg ◽

Jun Zhu ◽

Murray K. Clayton ◽

Monika E. Shea ◽

David J. Mladenoff

Keyword(s):

Random Field ◽

Markov Random Field ◽

Tree Species ◽

Forest Communities ◽

Field Approach ◽

Markov Random ◽

Historical Forest

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Dense Photometric Stereo: A Markov Random Field Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2006.224 ◽

2006 ◽

Vol 28 (11) ◽

pp. 1830-1846 ◽

Cited By ~ 44

Author(s):

Tai-Pang Wu ◽

Kam-Lun Tang ◽

Chi-Keung Tang ◽

Tien-Tsin Wong

Keyword(s):

Random Field ◽

Markov Random Field ◽

Photometric Stereo ◽

Field Approach ◽

Markov Random

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Supervised Classification of Social Spammers using a Similarity-based Markov Random Field Approach

Proceedings of the 5th Multidisciplinary International Social Networks Conference on - MISNC '18 ◽

10.1145/3227696.3227712 ◽

2018 ◽

Author(s):

Nour El-Mawass ◽

Paul Honeine ◽

Laurent Vercouter

Keyword(s):

Random Field ◽

Markov Random Field ◽

Supervised Classification ◽

Field Approach ◽

Markov Random

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