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An adaptive global–local approach for phase-field modeling of anisotropic brittle fracture
Alberto Silvio Chiappa, Stefano Micheletti, Riccardo Peli and Simona Perotto Communications in Nonlinear Science and Numerical Simulation 74 147 (2019) https://doi.org/10.1016/j.cnsns.2019.03.010
Discrete stochastic approximations of the Mumford–Shah functional
Energy approach to brittle fracture in strain-gradient modelling
Luca Placidi and Emilio Barchiesi Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 474(2210) 20170878 (2018) https://doi.org/10.1098/rspa.2017.0878
Crack nucleation in variational phase-field models of brittle fracture
Hybrid adaptation for detecting skin in color images
Michal Kawulok, Jolanta Kawulok, Jakub Nalepa, Bogdan Smolka and Eduardo Bayro-Corrochano Intelligent Data Analysis 20(s1) S121 (2016) https://doi.org/10.3233/IDA-160850
A higher-order phase-field model for brittle fracture: Formulation and analysis within the isogeometric analysis framework
Michael J. Borden, Thomas J.R. Hughes, Chad M. Landis and Clemens V. Verhoosel Computer Methods in Applied Mechanics and Engineering 273 100 (2014) https://doi.org/10.1016/j.cma.2014.01.016
An augmented-Lagrangian method for the phase-field approach for pressurized fractures
Crack patterns obtained by unidirectional drying of a colloidal suspension in a capillary tube: experiments and numerical simulations using a two-dimensional variational approach
A phase-field description of dynamic brittle fracture
Michael J. Borden, Clemens V. Verhoosel, Michael A. Scott, Thomas J.R. Hughes and Chad M. Landis Computer Methods in Applied Mechanics and Engineering 217-220 77 (2012) https://doi.org/10.1016/j.cma.2012.01.008
A discretization method for the numerical solution of Dieudonné–Rashevsky type problems with application to edge detection within noisy image data
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The Mumford–Shah variational model for image segmentation: An overview of the theory, implementation and use
Variational Models and Methods in Solid and Fluid Mechanics
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Alexandru Telea, Tobias Preusser, Christoph Garbe, Marc Droske and Martin Rumpf Lecture Notes in Computer Science, Pattern Recognition 4174 525 (2006) https://doi.org/10.1007/11861898_53
Image segmentation based on Mumford-Shah functional