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Max Mignotte
Max Mignotte
Professor of Computer Science, DIRO, Montreal University
Verified email at iro.umontreal.ca - Homepage
Title
Cited by
Cited by
Year
‘Unsupervised restoration of brain SPECT volumes
M Mignotte, J Meunier
Vision Interfaces (VI 2000), Montreal, Canada, 55-60, 2000
32000
3D biplanar reconstruction of lower limbs using nonlinear statistical models
DCT Nguyen, S Benameur, M Mignotte, F Lavoie
Medical & Biological Engineering & Computing 61 (11), 2877-2894, 2023
22023
3D biplanar reconstruction of scoliotic rib cage using statistical models
S Benameur, M Mignotte, F Destrempes, JA de Guise
2004
3D biplanar reconstruction of scoliotic vertebrae using statistical models
S Benameur, M Mignotte, S Parent, H Labelle, W Skalli, JA De Guise
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision …, 2001
432001
3D biplanar statistical reconstruction of scoliotic vertebrae
S Benameur, M Mignotte, S Parent, H Labelle, W Skalli, JA De Guise
Research into Spinal Deformities 4, 281-285, 2002
82002
3D/2D registration and segmentation of scoliotic vertebrae using statistical models
S Benameur, M Mignotte, S Parent, H Labelle, W Skalli, J de Guise
Computerized Medical Imaging and Graphics 27 (5), 321-337, 2003
2512003
A bicriteria-optimization-approach-based dimensionality-reduction model for the color display of hyperspectral images
M Mignotte
IEEE Transactions on Geoscience and Remote Sensing 50 (2), 501-513, 2011
422011
A biologically inspired framework for contour detection
M Mignotte
Pattern Analysis and Applications 20, 365-381, 2017
112017
A circular invariant convolution model-based mapping for multimodal change detection
R Touati, M Mignotte, M Dahmane
Adv. Sci., Technol. Eng. Syst. J. 5 (5), 1288-1298, 2020
32020
A comparison of supervised and blind deconvolution techniques applied in SPECT imagery
M Mignotte, J Meunier
Département D’informatique et de Reserche Opérationnelle (DIOR), Université …, 1999
51999
A consensus framework for segmenting video with dynamic textures
L Khelifi, M Mignotte
2018 15th IEEE International Conference on Advanced Video and Signal Based …, 2018
32018
A contrario edge detection with edgelets
N Widynski, M Mignotte
2011 IEEE International Conference on Signal and Image Processing …, 2011
172011
A de-texturing and spatially constrained K-means approach for image segmentation
M Mignotte
Pattern Recognition Letters 32 (2), 359-367, 2011
872011
A fractal projection and Markovian segmentation-based approach for multimodal change detection
M Mignotte
IEEE Transactions on Geoscience and Remote Sensing 58 (11), 8046-8058, 2020
632020
A hierarchical graph-based Markovian clustering approach for the unsupervised segmentation of textured color images
R Hedjam, M Mignotte
2009 16th IEEE International Conference on Image Processing (ICIP), 1365-1368, 2009
432009
A hierarchical statistical modeling approach for the unsupervised 3-D biplanar reconstruction of the scoliotic spine
S Benameur, M Mignotte, H Labelle, JA De Guise
IEEE Transactions on Biomedical Engineering 52 (12), 2041-2057, 2005
1262005
A hierarchical statistical modeling approach for the unsupervised 3D reconstruction of the scoliotic spine
S Benameur, M Mignotte, S Parent, H Labelle, W Skalli, JA De Guise
Proceedings 2003 International Conference on Image Processing (Cat. No …, 2003
172003
A hierarchical visual feature-based approach for image sonification
OK Toffa, M Mignotte
IEEE Transactions on Multimedia 23, 706-715, 2020
62020
A label field fusion Bayesian model and its penalized maximum rand estimator for image segmentation
M Mignotte
IEEE Transactions on Image Processing 19 (6), 1610-1624, 2010
1122010
A label field fusion model with a variation of information estimator for image segmentation
M Mignotte
Information Fusion 20, 7-20, 2014
542014
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