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2. Fast Style Transfer
- Author
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David Paper
- Subjects
Style (visual arts) ,Reference image ,Character (computing) ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Art ,ComputingMethodologies_COMPUTERGRAPHICS ,Visual arts ,Image (mathematics) ,media_common - Abstract
Neural style transfer (NST) is a computer vision technique that takes two images – a content image and a style reference image – and blends them together so that the resulting output image retains the core elements of the content image but appears to be painted in the style of the style reference image. The output image from a NST network is called a pastiche. A pastiche is a work of visual art, literature, theater or music that imitates the style (or character) of the work of one or more other artists. Unlike a parody, a pastiche celebrates rather than mocks the work it imitates.
- Published
- 2021
- Full Text
- View/download PDF
3. Geometry description and mesh construction from medical imaging
- Author
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Silvia Bertoluzza, Minh Phan, Michela Spagnuolo, Philippe Ricka, Micol Pennacchio, Giuseppe Patanè, Michele Giuliano Carlino, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Modeling Enablers for Multi-PHysics and InteractionS (MEMPHIS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut de Recherche Mathématique Avancée (IRMA), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Institut de Mathématiques de Toulon - EA 2134 (IMATH), Université de Toulon (UTLN), Istituto di Matematica Applicata e Tecnologie Informatiche (IMATI), Consiglio Nazionale delle Ricerche (CNR), Istituto di Matematica Applicata e Tecnologie Informatiche (IMATI-CNR), Consiglio Nazionale delle Ricerche [Roma] (CNR), his paper has been realized in the framework of ERC Project CHANGE, which has received funding from the EuropeanResearch Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No694515., European Project: 8509436(1986), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), and National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)
- Subjects
T57-57.97 ,Applied mathematics. Quantitative methods ,Computer simulation ,Computer science ,business.industry ,Atlas (topology) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image segmentation ,Modular design ,Reference image ,N/A ,QA1-939 ,Medical imaging ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging ,A priori and a posteriori ,Computer vision ,[INFO]Computer Science [cs] ,Artificial intelligence ,business ,Mathematics ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
International audience; We present a new method for defining and meshing patient-specific domains from medical images. Our approach is based on an atlas image segmentation technique, and relies on the modular registration algorithm of S. Bertoluzza et al. [25]. The mesh of the patient-specific domain is generated by deforming the corresponding mesh on an a priori segmented and meshed reference image (the atlas). Our method aims at automating the process at the interface of medical imaging and numerical simulation, thus reducing the computational cost in those situations where simulations have to be managed on numerous medical images of similar patients.; Nous présentons une nouvelle méthode de reconnaissance et de maillage d’un domaine d’intérêt d’une image médicale. Notre approche se base sur une méthode de segmentation à partir d’un atlas, et dépend de la boîte à outils modulaire pour la co-registration d’images développée par S. Bertoluzza et al. [25]. Le maillage du domaine spécifique au patient est généré par déformation du maillage correspondant sur une image de référence segmentée a priori (l’atlas). Notre méthode vise à automatiser le processus à l’interface entre l’imagerie médicale et la simulation numérique, avec pour but de réduire le coût de calcul dans les situations dans lesquelles des simulations doivent être faites sur de nombreuses images similaires.
- Published
- 2020
- Full Text
- View/download PDF
4. A hybrid high-order method for flow simulations in discrete fracture networks
- Author
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Florent Hédin, Géraldine Pichot, Alexandre Ern, Simulation for the Environment: Reliable and Efficient Numerical Algorithms (SERENA), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS), École des Ponts ParisTech (ENPC), This research has been partially supported by the LABEX AMIES ANR-10-LBX-0002-01 project.The authors are grateful to the LabCom fractory (CNRS,Université de Rennes 1 and Itasca Consultants) for providing the geometry and transmissivitydata for all the DFN considered in this paper. The authors warmly thank Nicolas Pignet (EDF)for many fruitful discussions related to DiSk++. Part of the simulations presented in thispaper were carried out using the PlaFRIM experimental testbed, supported by Inria, CNRS(LABRI and IMB), Université de Bordeaux, Bordeaux INP and Conseil Régional d’Aquitaine(see https://www.plafrim.fr/)., This research has been partially supported by the LABEX AMIES ANR-10-LBX-0002-01 project., and Hédin, Florent
- Subjects
Discrete fracture ,Materials science ,business.industry ,ComputingMethodologies_SIMULATIONANDMODELING ,010103 numerical & computational mathematics ,Mechanics ,[MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA] ,01 natural sciences ,010101 applied mathematics ,Permeability (earth sciences) ,Software ,Flow (mathematics) ,Fracture (geology) ,0101 mathematics ,High order ,business ,[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA] ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
International audience; We are interested in solving flow in large trimensional Discrete Fracture Networks (DFN) with the hybrid high-order (HHO) method. The objectives of this paper are: (1) to demonstrate the benefit of using a high-order method for computing macroscopic quantities, like the equivalent permeability of fracture rocks; (2) to present the computational efficiency of our C++ software, NEF++, which implements the solving of flow in fractures based on the HHO method.
- Published
- 2019
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