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Related papers: Model Simplification through refinement

200 papers

Computer model calibration is a crucial step in building a reliable computer model. In the face of massive physical observations, a fast estimation for the calibration parameters is urgently needed. To alleviate the computational burden, we…

Statistics Theory · Mathematics 2022-11-24 Shurui Lv , Yan Wang , Jun Yu

In the present work we introduce a novel refinement algorithm for two-dimensional elliptic partial differential equations discretized with Virtual Element Method (VEM). The algorithm improves the numerical solution accuracy and the mesh…

Numerical Analysis · Mathematics 2024-03-18 Stefano Berrone , Fabio Vicini

Surface reconstruction with preservation of geometric features is a challenging computer vision task. Despite significant progress in implicit shape reconstruction, state-of-the-art mesh extraction methods often produce aliased,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Natalia Soboleva , Olga Gorbunova , Maria Ivanova , Evgeny Burnaev , Matthias Nießner , Denis Zorin , Alexey Artemov

We present a novel algorithm to compute multi-scale curvature fields on triangle meshes. Our algorithm is based on finding robust mean curvatures using the ball neighborhood, where the radius of a ball corresponds to the scale of the…

Graphics · Computer Science 2016-11-01 Patrick Seemann , Simon Fuhrmann , Stefan Guthe , Fabian Langguth , Michael Goesele

Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can lead to overfitting, i.e. using a overly complicated model to…

Graphics · Computer Science 2017-09-06 Lin Gao , Yu-Kun Lai , Jie Yang , Ling-Xiao Zhang , Leif Kobbelt , Shihong Xia

Optimization-based solvers play a central role in a wide range of signal processing and communication tasks. However, their applicability in latency-sensitive systems is limited by the sequential nature of iterative methods and the high…

Signal Processing · Electrical Eng. & Systems 2026-03-12 Dvir Avrahami , Amit Milstein , Caroline Chaux , Tirza Routtenberg , Nir Shlezinger

We refine the bit complexity analysis of an algorithm for the computation of at least one point per connected component of a smooth real algebraic set, yielding exponential speedup (with respect to the number of variables) compared to prior…

Symbolic Computation · Computer Science 2025-08-29 Jesse Elliott , Mark Giesbrecht , Edern Gillot , Mohab Safey El Din , Éric Schost

We describe a new algorithm to compute the geometric intersection number between two curves, given as edge vectors on an ideal triangulation. Most importantly, this algorithm runs in polynomial time in the bit-size of the two edge vectors.…

Geometric Topology · Mathematics 2016-05-12 Mark C. Bell , Richard C. H. Webb

Computational analysis with the finite element method requires geometrically accurate meshes. It is well known that high-order meshes can accurately capture curved surfaces with fewer degrees of freedom in comparison to low-order meshes.…

Mathematical Software · Computer Science 2024-01-30 Ketan Mittal , Veselin A. Dobrev , Patrick Knupp , Tzanio Kolev , Franck Ledoux , Claire Roche , Vladimir Z. Tomov

Modeling of physical systems includes extensive use of software packages that implement the accurate finite element method for solving differential equations considered along with the appropriate initial and boundary conditions. When the…

Computational Engineering, Finance, and Science · Computer Science 2018-03-20 O. Kononenko , I. Kononenko

The era of huge data necessitates highly efficient machine learning algorithms. Many common machine learning algorithms, however, rely on computationally intensive subroutines that are prohibitively expensive on large datasets. Oftentimes,…

Machine Learning · Computer Science 2023-09-26 Mo Tiwari

Simplification is one of the fundamental operations used in geoinformation science (GIS) to reduce size or representation complexity of geometric objects. Although different simplification methods can be applied depending on one's purpose,…

Computational Geometry · Computer Science 2020-01-17 Joon-Seok Kim , Carola Wenk

Kernel pruning methods have been proposed to speed up, simplify, and improve explanation of convolutional neural network (CNN) models. However, the effectiveness of a simplified model is often below the original one. In this letter, we…

Machine Learning · Computer Science 2021-08-19 D. Osaku , J. F. Gomes , A. X. Falcão

We present a novel coarse-to-fine framework that derives a semi-regular multiscale mesh representation of an original input mesh via remeshing. Our approach differs from the conventional mesh wavelet transform strategy in two ways. First,…

Image and Video Processing · Electrical Eng. & Systems 2018-10-09 Hao-Chiang Shao

Plane arrangements are a useful tool for surface and volume modelling. However, their main drawback is poor scalability. We introduce two key novelties that enable the construction of plane arrangements for complex objects and entire…

Computational Geometry · Computer Science 2024-07-12 Raphael Sulzer , Florent Lafarge

This paper propose a interactive 3D modeling method and corresponding system based on single or multiple uncalibrated images. The main feature of this method is that, according to the modeling habits of ordinary people, the 3D model of the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhi He , Rui Wang , Wei Hua , Yuchi Huo

In real case applications within the virtual prototyping process, it is not always possible to reduce the complexity of the physical models and to obtain numerical models which can be solved quickly. Usually, every single numerical…

Machine Learning · Computer Science 2024-08-29 Thomas Most , Johannes Will

We present an optimization procedure for generic polygonal or polyhedral meshes, tailored for the Virtual Element Method (VEM). Once the local quality of the mesh elements is analyzed through a quality indicator specific to the VEM, groups…

Numerical Analysis · Mathematics 2024-11-08 Tommaso Sorgente , Stefano Berrone , Silvia Biasotti , Gianmarco Manzini , Michela Spagnuolo , Fabio Vicini

Several explainable AI methods allow a Machine Learning user to get insights on the classification process of a black-box model in the form of local linear explanations. With such information, the user can judge which features are locally…

Machine Learning · Computer Science 2023-02-16 Francesco Lomuscio , Paolo Bajardi , Alan Perotti , Elvio G. Amparore

A recent trend in deep learning algorithms has been towards training large scale models, having high parameter count and trained on big dataset. However, robustness of such large scale models towards real-world settings is still a…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Nishant Jain , Harkirat Behl , Yogesh Singh Rawat , Vibhav Vineet