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Publications

Cette page présente les publications du Centre Borelli déposées sur le serveur HAL.

Affichage des publications 1001 à 1010 sur 1468 au total

Computer Science

Power Attributed Graph Embedding and Clustering

Representation learning is a central problem of Attributed Networks data analysis in a variety of fields. Given an attributed graph, the objectives are to obtain a representation of nodes and a partition of the set of nodes. Usually these two…

Lazhar Labiod, Mohamed Nadif

IEEE Transactions on Neural Networks and Learning Systems -

Mathematics

Measurement of Bridge Vibration by UAVs Combined with CNN and KLT Optical-Flow Method

A measurement method of bridge vibration by unmanned aerial vehicles (UAVs) combined with convolutional neural networks (CNNs) and Kanade-Lucas-Tomasi (KLT) optical-flow method is proposed. In this method, the stationary reference points in the…

Zhaocheng Yan, Zihan Jin, Shuai Teng, Gongfa Chen, David Bassir

Applied Sciences -

Bioengineering

Assessing Smoothness of Arm Movements With Jerk: A Comparison of Laterality, Contraction Mode and Plane of Elevation. A Pilot Study

Measuring the quality of movement is a need and a challenge for clinicians. Jerk, defined as the quantity of acceleration variation, is a kinematic parameter used to assess the smoothness of movement. We aimed to assess and compare jerk metrics in…

Alexandra Roren, Antoine Mazarguil, Diego Vaquero-Ramos, Jean-Baptiste Deloose, Pierre-Paul Vidal, Christelle Nguyen, François Rannou, Danping Wang, Laurent Oudre, Marie-Martine Lefèvre-Colau

Frontiers in Bioengineering and Biotechnology -

Machine Learning

TensorClus: A python library for tensor (Co)-clustering

Tensor data analysis is the evolutionary step of data analysis to more than two dimensions. Dealing with tensor data is often based on tensor decomposition methods. The present paper focuses on unsupervised learning and provides a python package…

Rafika Boutalbi, Lazhar Labiod, Mohamed Nadif

Neurocomputing -

Signal and Image processing

An Uncertainty Principle for Lowband Graph Signals

In this article, we introduce a novel lower bound on the support size of lowband graph signals. This result allows the deduction of an optimality criterion for the lowband and sparse decomposition of any graph signal, establishing the uniqueness of…

Antoine Mazarguil, Laurent Oudre, Nicolas Vayatis

IEEE Signal Processing Letters -

Life Sciences

The role of irinotecan-bevacizumab as rescue regimen in children with low-grade gliomas: a retrospective nationwide study in 72 patients

Introduction : At least half of children with low-grade glioma (LGG) treated with first line chemotherapy experience a relapse/progression and may therefore need a second-line chemotherapy. Irinotecan-bevacizumab has been recommended in this setting…

Charles de Marcellus, Arnault Tauziède-Espariat, Aurélie Cuinet, Claudia Pasqualini, Matthieu Robert, Kevin Beccaria, Stéphanie Puget, Nathalie Boddaert, Dominique Figarella-Branger, Emilie de Carli, Franck Bourdeaut, Pierre Leblond, Fanny Fouyssac, Nicolas Andre, Anne Bertozzi, Thibaut Butel, Christelle Dufour, Dominique Valteau-Couanet, Pascale Varlet, Jacques Grill

Journal of Neuro-Oncology -

Signal and Image processing

Non-smooth interpolation of graph signals

We consider the problem of signal interpolation on graphs, i.e. recovering one or multiple graph signal values from incomplete measurements. We propose a review of the graph signal interpolation methods, which enlightens the restrictive underlying…

Antoine Mazarguil, Laurent Oudre, Nicolas Vayatis

Signal Processing -

Optimization and Control

Improving NMF clustering by leveraging contextual relationships among words

Non-negative Matrix Factorization (NMF) and its variants have been successfully used for clustering text documents. However, NMF approaches like other models do not explicitly account for the contextual dependencies between words. To remedy this…

Mickael Febrissy, Aghiles Salah, Melissa Ailem, Mohamed Nadif

Neurocomputing -