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The described works have been carried out in the framework of a mid-term study initiated by the Centre Electronique de l'Armement and led by ADERSA, a French company of research under contract. The aim was to study the techniques of regular…

Computer Vision and Pattern Recognition · Computer Science 2016-05-06 Olivier Guye

This last document is showing the gradual introduction of hierarchical modeling techniques in image analysis. The first chapter is dealing with the first works carried out in the field of industrial applications of pattern recognition. The…

Computer Vision and Pattern Recognition · Computer Science 2016-05-05 Olivier Guye

This article describes a geometric partitioning software that can be used for quick computation of data partitions on many-core HPC machines. It is most suited for dynamic applications with load distributions that vary with time.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-19 Aparna Sasidharan

While deep learning excels in natural image and language processing, its application to high-dimensional data faces computational challenges due to the dimensionality curse. Current large-scale data tools focus on business-oriented…

Machine Learning · Computer Science 2025-07-01 Chen Zhang

The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-07 Roman Voliansky , Andri Pranolo

To prepare images for better segmentation, we need preprocessing applications, such as smoothing, to reduce noise. In this paper, we present an enhanced computation method for smoothing 2D object in binary case. Unlike existing approaches,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-31 Ramzi Mahmoudi , Mohamed Akil

Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the potential for energy-efficient high-performance, such potential…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-11 Jianbin Fang , Chun Huang , Tao Tang , Zheng Wang

Multi-core architectures feature an intricate hierarchy of cache memories, with multiple levels and sizes. To adequately decompose an application according to the traits of a particular memory hierarchy is a cumbersome task that may be…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-20 Hervé Paulino , Nuno Delgado

This fourth and last tome is focusing on describing the envisioned works for a project that has been presented in the preceding tome. It is about a new approach dedicated to the coding of still and moving pictures, trying to bridge the…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Olivier Guye

The problem of decomposing non-manifold object has already been studied in solid modeling. However, the few proposed solutions are limited to the problem of decomposing solids described through their boundaries. In this thesis we study the…

Graphics · Computer Science 2019-04-03 Franco Morando

Complex geometric tasks such as geometric modeling, physical simulation, and texture parametrization often involve the embedding of many complex sub-domains with potentially different dimensions. These tasks often require evolving the…

Graphics · Computer Science 2025-01-03 Michael Tao , Jiacheng Dai , Denis Zorin , Teseo Schneider , Daniele Panozzo

Smoothing filter is the method of choice for image preprocessing and pattern recognition. We present a new concurrent method for smoothing 2D object in binary case. Proposed method provides a parallel computation while preserving the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-01 Ramzi Mahmoudi , Mohamed Akil

Heterogeneous object design is an active research area in recent years. The conventional CAD modeling approaches only provide geometry and topology of the object, but do not contain any information with regard to the materials of the object…

Computational Engineering, Finance, and Science · Computer Science 2010-04-22 Vikas Gupta , K. S. Kasana , Puneet Tandon

Hyperdimensional (HD) computing is a set of neurally inspired methods for obtaining high-dimensional, low-precision, distributed representations of data. These representations can be combined with simple, neurally plausible algorithms to…

Machine Learning · Computer Science 2022-02-21 Anthony Thomas , Sanjoy Dasgupta , Tajana Rosing

Deep learning methods have been successfully applied to various computer vision tasks. However, existing neural network architectures do not per se incorporate domain knowledge about the addressed problem, thus, understanding what the model…

Computer Vision and Pattern Recognition · Computer Science 2019-10-21 Iman Marivani , Evaggelia Tsiligianni , Bruno Cornelis , Nikos Deligiannis

Modern information processing relies on the axiom that high-dimensional data lie near low-dimensional geometric structures. This paper revisits the problem of data-driven learning of these geometric structures and puts forth two new…

Machine Learning · Statistics 2018-03-06 Tong Wu , Waheed U. Bajwa

The focus of this article is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of…

Discrete Mathematics · Computer Science 2014-02-19 V. Bino Sebastian , A Unnikrishnan , Kannan Balakrishnan , P. B Ramkumar

We address in this thesis the current need to design new parallel algorithms and tools that ease the development of geodynamic modelling applications that are suited for today's and tomorrow's hardware. We present (1) the MATLAB HPC…

Geophysics · Physics 2022-07-19 Samuel Omlin , Ludovic Räss , Benjamin Malvoisin , Yury Y. Podladchikov

In a world abundant with diverse data arising from complex acquisition techniques, there is a growing need for new data analysis methods. In this paper we focus on high-dimensional data that are organized into several hierarchical datasets.…

Machine Learning · Computer Science 2021-04-06 Lior Aloni , Omer Bobrowski , Ronen Talmon

This paper introduces a new discrete fracture model accounting for non-isothermal compositional multiphase Darcy flows and complex networks of fractures with intersecting, immersed and non immersed fractures. The so called…

Numerical Analysis · Mathematics 2017-07-13 Feng Xing , Roland Masson , Simon Lopez
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