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Publications

 

Les publications de nos enseignants-chercheurs sont sur la plateforme HAL :

 

Les publications des thèses des docteurs du LTCI sont sur la plateforme HAL :

 

Retrouver les publications figurant dans l'archive ouverte HAL par année :

2017

  • Les facettes de l'Open Data : émergence, fondements et travail en coulisses
    • Denis Jérôme
    • Goëta Samuel
    , 2017, pp.121-138. Dans ce chapitre, nous revenons sur l'émergence des politiques d'open data en mettant en lumière les grands principes (de la transparence jusqu'à la modernisation de l'administration, en passant par la libre circulation de l'information) que différentes initiatives ont progressivement stabilisés pour faire de l'ouverture des données publiques un enjeu international. Nous montrons ensuite, à partir d'une enquête ethnographique menée dans plusieurs institutions françaises ce que cette ouverture implique concrètement : un travail délicat qui demeure largement invisible et représente le coût caché des principes fondateurs de l'open data.
  • Towards building 3D individual models from MRI segmentation and tractography to enhance surgical planning for pediatric pelvic tumors and malformations
    • Muller Cécile
    • Virzi Alessio
    • Marret Jean-Baptiste
    • Mille Eva
    • Berteloot Laureline
    • Grevent David
    • Blanc Thomas
    • Garcelon Nicolas
    • Buffet Isabelle
    • Hullier-Ammard Elisabeth
    • Gori Pietro
    • Boddaert Nathalie
    • Bloch Isabelle
    • Sarnacki Sabine
    , 2017, pp.113-115.
  • La fabrique des données brutes. Le travail en coulisses de l'open data
    • Denis Jérôme
    • Goëta Samuel
    , 2017. Depuis quelques années, les initiatives d’open data se sont multipliées à travers le monde. Présentées jusque dans la presse grand public comme une ressource inexploitée, le « pétrole » sur lequel le monde serait assis, les données publiques sont devenues objet de toutes les attentions et leur ouverture porteuse de toutes les promesses, à la fois terreau d’un renouveau démocratique et moteur d’une innovation distribuée. Comme dans les sciences, qui ont connu un mouvement de focalisation similaire sur les données et leur partage, l’injonction à l’ouverture opère une certaine mise en invisibilité. Le vocabulaire de la « libération », de la « transparence » et plus encore celui de la « donnée brute » efface toute trace des conditions de production des données, des contextes de leurs usages initiaux et pose leur universalité comme une évidence. Ce chapitre explore les coulisses de l’open data afin de retrouver les traces de cette production et d’en comprendre les spécificités. À partir d’une série d’entretiens ethnographiques dans diverses institutions, il décrit la fabrique des données brutes, dont l’ouverture ne se résume jamais à une mise à disponibilité immédiate, évidente et universelle. Il montre que trois aspects sont particulièrement sensibles dans le processus d’ouverture : l’identification, l'extraction et la « brutification » des données. Ces trois séries d’opérations donnent à voir l’épaisseur sociotechnique des données brutes dont la production mêle dimensions organisationnelles, politiques et techniques.
  • Trends in Social Network Analysis - Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
    • Missaoui Rokia
    • Abdessalem Talel
    • Latapy Mathieu
    , 2017, pp.255. <p>The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.</p> <p> </p> (10.1007/978-3-319-53420-6)
    DOI : 10.1007/978-3-319-53420-6
  • Using modular extension to provably protect Edwards curves against fault attacks
    • Dugardin Margaux
    • Guilley Sylvain
    • Moreau Martin
    • Najm Zakaria
    • Rauzy Pablo
    Journal of Cryptographic Engineering, Springer, 2017, vol. 7, nb. 4.
  • Multiview approaches to event detection and scene analysis
    • Essid Slim
    • Parekh Sanjeel
    • Duong Ngoc Q. K.
    • Serizel Romain
    • Ozerov Alexey
    • Antonacci Fabio
    • Sarti Augusto
    , 2017, pp.243-276. This chapter addresses sound scene and event classification in multiview settings, that is, settings where the observations are obtained from multiple sensors, each sensor contributing a particular view of the data (e.g., audio microphones, video cameras, etc.). We briefly introduce some of the techniques that can be exploited to effectively combine the data conveyed by the different views under analysis for a better interpretation. We first provide a high-level presentation of generic methods that are particularly relevant in the context of multiview and multimodal sound scene analysis. Then, we more specifically present a selection of techniques used for audiovisual event detection and microphone array-based scene analysis. (10.1007/978-3-319-63450-0_9)
    DOI : 10.1007/978-3-319-63450-0_9
  • Convergence to multi-resource fairness under end-to-end window control
    • Bonald Thomas
    • Roberts James
    • Vitale Christian
    , 2017. The paper relates to multi-resource sharing between flows with heterogeneous requirements as arises in networks with wireless links or software routers implementing network function virtualization. Bottleneck max fairness (BMF) is a sharing objective in this context with good performance. The paper shows that BMF results when local fairness is imposed at each resource while flow rates are controlled by an end-to-end window. We analytically prove convergence to BMF under a fluid model when flows share a network limited to 2 resources while numerical results confirm BMF convergence for larger networks. Simulation results illustrate the impact of packetized transmission.
  • Towards the Generation of Expressive Co-Speech Gestures
    • Ravenet Brian
    • Clavel Chloé
    • Pelachaud Catherine I
    , 2017.
  • Acoustic Features for Environmental Sound Analysis
    • Serizel Romain
    • Bisot Victor
    • Essid Slim
    • Richard Gael
    , 2017, pp.71-101. Most of the time it is nearly impossible to differentiate between particular type of sound events from a waveform only. Therefore, frequency domain and time-frequency domain representations have been used for years providing representations of the sound signals that are more inline with the human perception. However, these representations are usually too generic and often fail to describe specific content that is present in a sound recording. A lot of work have been devoted to design features that could allow extracting such specific information leading to a wide variety of hand-crafted features. During the past years, owing to the increasing availability of medium scale and large scale sound datasets, an alternative approach to feature extraction has become popular, the so-called feature learning. Finally, processing the amount of data that is at hand nowadays can quickly become overwhelming. It is therefore of paramount importance to be able to reduce the size of the dataset in the feature space. The general processing chain to convert an sound signal to a feature vector that can be efficiently exploited by a classifier and the relation to features used for speech and music processing are described is this chapter. (10.1007/978-3-319-63450-0_4)
    DOI : 10.1007/978-3-319-63450-0_4
  • Balanced Fair Resource Sharing in Computer Clusters
    • Bonald Thomas
    • Comte Céline
    Performance Evaluation, Elsevier, 2017. We represent a computer cluster as a multi-server queue with some arbitrary graph of compatibilities between jobs and servers. Each server processes its jobs sequentially in FCFS order. The service rate of a job at any given time is the sum of the service rates of all servers processing this job. We show that the corresponding queue is quasi-reversible and use this property to design a scheduling algorithm achieving balanced fair sharing of the computing resources. (10.1016/j.peva.2017.08.006)
    DOI : 10.1016/j.peva.2017.08.006
  • Parameter Sensitivity Analysis of the Energy/Frequency Convexity Rule for Nanometer-scale Application Processors
    • de Vogeleer Karel
    • Memmi Gerard
    • Jouvelot Pierre
    Sustainable Computing : Informatics and Systems, Elsevier, 2017, 15, pp.16-27. Both theoretical and experimental evidence are presented in this work in order to validate the existence of an Energy/Frequency Convexity Rule, which relates energy consumption and microprocessor frequency for nanometer-scale microprocessors. Data gathered during several month-long experimental acquisition campaigns, supported by several independent publications, suggest that energy consumed is indeed depending on the microprocessor's clock frequency, and, more interestingly, the curve exhibits a clear minimum over the processor's frequency range. An analytical model for this behavior is presented and motivated, which fits well with the experimental data. A parameter sensitivity analysis shows how parameters affect the energy minimum in the clock frequency space. The conditions are discussed under which this convexity rule can be exploited, and when other methods are more effective, with the aim of improving the computer system's energy management efficiency. We show that the power requirements of the computer system, besides the microprocessor, and the overhead affect the location of the energy minimum the most. The sensitivity analysis of the Energy/Frequency Convexity Rule puts forward a number of simple guidelines especially for by low-power systems, such as battery-powered and embedded systems, and less likely by high-performance computer systems. (10.1016/j.suscom.2017.05.001)
    DOI : 10.1016/j.suscom.2017.05.001
  • Goal-oriented Holonic Systems
    • Diaconescu Ada
    , 2017, pp.209-258.
  • Towards a framework for the levels and aspects of selfaware computing systems
    • Lewis Peter
    • Bellman Kirstie
    • Landauer Chris
    • Esterle Lukas
    • Glette Kyrre
    • Diaconescu Ada
    • Giese Holger
    , 2017, pp.51-85.
  • FDOPA Patterns in Adrenal Glands
    • Moreau Aurélie
    • Giraudet Anne Laure
    • Kryza David
    • Borson-Chazot Françoise
    • Bournaud-Salinas Claire
    • Mognetti Thomas
    • Lifante Jean-Christophe
    • Combemale Patrick
    • Giammarile Francesco
    • Houzard Claire
    Clinical Nuclear Medicine, Lippincott, Williams & Wilkins, 2017, 42 (5), pp.379-382. (10.1097/RLU.0000000000001636)
    DOI : 10.1097/RLU.0000000000001636
  • On Stochastic Proximal Gradient Algorithms
    • Atchadé Y.
    • Fort Gersende
    • Moulines Eric
    Journal of Machine Learning Research, Microtome Publishing, 2017.
  • Repenser les médiations. Analyse des manières de faire découvrir et apprécier les œuvres et pratiques culturelles, de la production à la réception
    • Bonnéry Stéphane
    • Coavoux Samuel
    • Deslyper Rémi
    • Eloy Florence
    • Francois Sébastien
    • Giraud Frédérique
    • Legon Tomas
    • Mille Muriel
    , 2017.
  • Dispositif échantillonneur- bloqueur de signal électrique
    • Meyer A.
    • Louis B.
    • Corbière Rémi
    • Petit V.
    • Desgreys Patricia
    • Petit H.
    , 2017.
  • On metric convexity, the discrete Hahn-Banach theorem, separating systems and sets of points forming only acute angles
    • Randriambololona Hugues
    Int. J. of Information and Coding Theory, 2017, 4 (2/3), pp.159-169.
  • A top-down engineering curriculum and application to a French "grande école
    • Chinchilla Raphael
    • Rodriguez G.
    IEEE Transactions on Education, Institute of Electrical and Electronics Engineers, 2017.
  • Safe and Secure Support for Public Safety Networks
    • Apvrille Ludovic
    • Li Letitia W.
    , 2017, pp.185 - 210. <p>As explained by Tanzi et al. in the first volume of this book, communicating and autonomous devices will surely have a role to play in the future Public Safety Networks. The “communicating” feature comes from the fact that the information should be delivered in a fast way to rescuers. The “autonomous” characteristic comes from the fact that rescuers should not have to concern themselves about these objects: they should perform their mission autonomously so as not to delay the intervention of the rescuers, but rather to assist them efficiently and reliably.</p> (10.1016/B978-1-78548-053-9.50009-3)
    DOI : 10.1016/B978-1-78548-053-9.50009-3
  • Signal and quantum noise in optical communications and in cryptography
    • Gallion Philippe
    • Mendieta F J
    • Jiang Shifeng
    , 2017.
  • Exploring structure for long-term tracking of multiple objects in sports videos
    • Morimitsu Henrique
    • Bloch Isabelle
    • Cesar R. M.
    Computer Vision and Image Understanding, Elsevier, 2017, 159, pp.89-104. In this paper we propose a novel approach for exploring structural relations to track multiple objects that may undergo long-term occlusion and abrupt motion. We use a model-free approach that relies only on annotations given in the first frame of the video to track all the objects online, i.e. without knowledge from future frames. We initialize a probabilistic Attributed Relational Graph (ARG) from the first frame, which is incrementally updated along the video. Instead of using structural information only to evaluate the scene, the proposed approach considers it to generate new tracking hypotheses. In this way, our method is capable of generating relevant object candidates that are used to improve or recover the track of lost objects. The proposed method is evaluated on several videos of table tennis matches and on the ACASVA dataset. The results show that our approach is very robust, flexible and able to outperform other state-of-the-art methods in sports videos that present structural patterns.
  • Topological relations between bipolar fuzzy sets based on mathematical morphology
    • Bloch Isabelle
    , 2017, LNCS 10225, pp.40-51. In many domains of information processing, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools. Here we propose to extend these tools by defining set theoretical and topological relations between bipolar fuzzy sets, including intersection, inclusion, adjacency and RCC relations widely used in mereotopology, based on bipolar connectives and on mathematical morphology operators.
  • A new method based on template registration and deformable models for pelvic bones semi-automatic segmentation in pediatric MRI
    • Virzi Alessio
    • Marret Jean-Baptiste
    • Muller Cécile
    • Berteloot Laureline
    • Boddaert Nathalie
    • Sarnacki Sabine
    • Bloch Isabelle
    , 2017, pp.323-326. In this paper we address the problem of bone segmentation in MRI images of children, in the region of the pelvis. To cope with the complex structure of the bones in this region and their changing topology during growth, we propose a method relying on 3D bone templates. These models are built from 3D CT images. For a given MRI volume, the closest template is chosen and registered on the MRI data. This leads to an initial segmentation which is then refined using a deformable model approach, where the regularization parameters depend on the local curvature, and the landmarks used during the registration are fixed anchors during the deformation. This approach was successfully applied to 15 MRI volumes of children between 1 and 18 years old, with an average accuracy in terms of medium distance of M D = 1.17 ± 0.29 mm and Dice Index of DC = 0.81 ± 0.04.
  • Brain MRI Segmentation using Fully Convolutional Network and Transfer Learning
    • Xu Yongchao
    • Géraud Thierry
    • Puybareau Elodie
    • Bloch Isabelle
    , 2017.