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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

  • Classification of MRI data using deep learning and Gaussian process-based model selection
    • Bertrand Hadrien
    • Perrot Matthieu
    • Ardon Roberto
    • Bloch Isabelle
    , 2017, pp.745-748. The classification of MRI images according to the anatomical field of view is a necessary task to solve when faced with the increasing quantity of medical images. In parallel, advances in deep learning makes it a suitable tool for computer vision problems. Using a common architecture (such as AlexNet) provides quite good results, but not sufficient for clinical use. Improving the model is not an easy task, due to the large number of hyper-parameters governing both the architecture and the training of the network, and to the limited understanding of their relevance. Since an exhaustive search is not tractable, we propose to optimize the network first by random search, and then by an adaptive search based on Gaussian Processes and Probability of Improvement. Applying this method on a large and varied MRI dataset, we show a substantial improvement between the baseline network and the final one (up to 20% for the most difficult classes).
  • Fuzzy Skeleton and Skeleton by Influence Zones: A Review
    • Bloch Isabelle
    , 2017, pp.71-87. <p> Skeleton is a widely addressed topic in binary image processing and object or shape representation. The difficulty raised by the discrete nature of images has led to different classes of methods. Among the most popular ones, distance based methods led to the important notion of centers of maximal balls (CMB), and mathematical morphology based methods led both to an efficient computation of CMB and to a completely different class of approaches, relying on homotopic thinning. Skeleton by influence zones (SKIZ) is another important related problem, often addressed using tools from mathematical morphology.</p> <p> </p> <p>When imprecision has to be explicitly modeled, then objects become fuzzy sets and all the previous approaches for skeleton and SKIZ have to be extended to deal with fuzzy sets and to cope with spatial imprecision. This chapter gives an overview of the main existing definitions of fuzzy skeleton and fuzzy SKIZ, including some derived from grey level image processing, and proposes a few novel definitions. </p>
  • Yet another proof of the entropy power inequality
    • Rioul Olivier
    IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2017, 63 (6), pp.3595-3599. Yet another simple proof of the entropy power inequality is given, which avoids both the integration over a path of Gaussian perturbation and the use of Young’s inequality with sharp constant or Rényi entropies. The proof is based on a simple change of variables, is formally identical in one and several dimensions, and easily settles the equality case. (10.1109/TIT.2017.2676093)
    DOI : 10.1109/TIT.2017.2676093
  • Method, device, and computer program for transmitting portions of encapsulated media content
    • Denoual Franck
    • Mazé Frédéric
    • Ruellan Hervé
    • Le Feuvre J.
    • Ouedraogo Nael
    , 2017.
  • Very high resolution and interferometric SAR: Markovian and patch-based non-local mathematical models
    • Deledalle Charles-Alban
    • Denis Loïc
    • Ferraioli Giampaolo
    • Pascazio Vito
    • Schirinzi Gilda
    • Tupin Florence
    , 2017. This chapter is dedicated to very high resolution (VHR) SAR imagery, including interferometric applications. First, the principles of SAR data acquisition are presented as well as the different types of configurations. The widely adopted Gaussian complex model of fully developed speckle is described as well as more advanced statistical models for VHR SAR data that account for textures. The following two parts are devoted to SAR image estimation and to image denoising within two different frameworks. First, Markovian modeling is introduced and the associated optimization approaches are presented, including graph-cut based optimization. The second framework is the patch-based non-local modeling of SAR complex data. Both frameworks are adapted to SAR images through the use of statistical models specific to SAR imagery. Their applications to amplitude data, interferometry, and fusion with optical data are illustrated. A special focus is given to phase unwrapping applied to single and multi- channel interferometry, showing the usefulness of local and global contextual models. (10.1007/978-3-319-66330-2)
    DOI : 10.1007/978-3-319-66330-2
  • Autoreject: Automated artifact rejection for MEG and EEG data
    • Jas Mainak
    • Engemann Denis A
    • Bekhti Yousra
    • Raimondo Federico A
    • Gramfort Alexandre
    NeuroImage, Elsevier, 2017. We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals. Our method capitalizes on cross-validation in conjunction with a robust evaluation metric to estimate the optimal peak-to-peak threshold – a quantity commonly used for identifying bad trials in M/EEG. This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors. Depending on the number of bad sensors, the trial is then repaired by interpolation or by excluding it from subsequent analysis. All steps of the algorithm are fully automated thus lending itself to the name Autoreject. In order to assess the practical significance of the algorithm, we conducted extensive validation and comparisons with state-of-the-art methods on four public datasets containing MEG and EEG recordings from more than 200 subjects. The comparisons include purely qualitative efforts as well as quantitatively benchmarking against human supervised and semi-automated preprocessing pipelines. The algorithm allowed us to automate the preprocessing of MEG data from the Human Connectome Project (HCP) going up to the computation of the evoked responses. The automated nature of our method minimizes the burden of human inspection, hence supporting scalability and reliability demanded by data analysis in modern neuroscience. (10.1016/j.neuroimage.2017.06.030)
    DOI : 10.1016/j.neuroimage.2017.06.030
  • Large Scale Density-friendly Graph Decomposition via Convex Programming
    • Danisch Maximilien
    • Chan T-H. Hubert
    • Sozio Mauro
    , 2017.
  • Physical attacks
    • El Mrabet Nadia
    • Goubin Louis
    • Fournier Jacques Jean-Alain
    • Jauvart Damien
    • Guilley Sylvain
    • Moreau Martin
    • Rauzy Pablo
    • Rondepierre Franck
    , 2017.
  • Nonequilibrium Green's functions theory for the alpha factor of quantum cascade lasers
    • Pereira Mauro
    • Winge David
    • Wacker Andreas
    • Jumpertz Louise
    • Michel Florian
    • Pawlus Robert
    • Elsassaer Wolfgang
    • Schires Kevin
    • Carras Mathieu
    • Grillot Frédéric
    , 2017.
  • Planck intermediate results - L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis
    • Aghanim N.
    • Ashdown M.
    • Aumont J.
    • Baccigalupi C.
    • Ballardini M.
    • Banday A.J.
    • Barreiro R.B.
    • Bartolo N.
    • Basak S.
    • Benabed K.
    • Bernard Jean-Paul
    • Bersanelli M.
    • Bielewicz P.
    • Bonaldi A.
    • Bonavera L.
    • Bond J.R.
    • Borrill J.
    • Bouchet F.R.
    • Boulanger F.
    • Bracco A.
    • Burigana C.
    • Calabrese E.
    • Cardoso J.F.
    • Chiang H.C.
    • Colombo L.P.L.
    • Combet C.
    • Comis B.
    • Crill B.P.
    • Curto A.
    • Cuttaia F.
    • Davis R.J.
    • de Bernardis P.
    • de Rosa A.
    • de Zotti G.
    • Delabrouille J.
    • Delouis J. M.
    • Di Valentino E.
    • Dickinson C.
    • Diego J.M.
    • Dore O.
    • Douspis M.
    • Ducout A.
    • Dupac X.
    • Dusini S.
    • Efstathiou G.
    • Elsner F.
    • Ensslin T.A.
    • Eriksen H.K.
    • Falgarone E.
    • Fantaye Y.
    • Finelli F.
    • Frailis M.
    • Fraisse A.A.
    • Franceschi E.
    • Frolov A.
    • Galeotta S.
    • Galli S.
    • Ganga K.
    • Genova-Santos R.T.
    • Gerbino M.
    • Ghosh T.
    • Giard M.
    • Gonzalez-Nuevo J.
    • Gorski K.M.
    • Gregorio A.
    • Gruppuso A.
    • Gudmundsson J.E.
    • Hansen F.K.
    • Helou G.
    • Herranz D.
    • Hivon E.
    • Huang Z.
    • Jaffe A.H.
    • Jones W.C.
    • Keihanen E.
    • Keskitalo R.
    • Kisner T.S.
    • Krachmalnicoff N.
    • Kunz M.
    • Kurki-Suonio H.
    • Lagache G.
    • Lahteenmaki A.
    • Lamarre J.M.
    • Lasenby A.
    • Lattanzi M.
    • Lawrence C.R.
    • Le Jeune M.
    • Levrier F.
    • Liguori M.
    • Lilje P.B.
    • Lopez-Caniego M.
    • Lubin P.M.
    • Macias-Perez J.F.
    • Maggio G.
    • Maino D.
    • Mandolesi N.
    • Mangilli A.
    • Maris M.
    • Martin P.G.
    • Martinez-Gonzalez E.
    • Matarrese S.
    • Mauri N.
    • Mcewen J.D.
    • Melchiorri A.
    • Mennella A.
    • Migliaccio M.
    • Mitra S.
    • Miville-Deschenes M.A.
    • Molinari D.
    • Moneti A.
    • Montier L.
    • Morgante G.
    • Moss A.
    • Naselsky P.
    • Norgaard-Nielsen H.U.
    • Oxborrow C.A.
    • Pagano L.
    • Paoletti D.
    • Partridge B.
    • Patrizii L.
    • Perdereau O.
    • Perotto L.
    • Pettorino V.
    • Piacentini F.
    • Plaszczynski S.
    • Polenta G.
    • Puget J.L.
    • Rachen J.P.
    • Reinecke M.
    • Remazeilles M.
    • Renzi A.
    • Rocha G.
    • Rossetti M.
    • Roudier G.
    • Rubino-Martin J.A.
    • Ruiz-Granados B.
    • Salvati L.
    • Sandri M.
    • Savelainen M.
    • Scott D.
    • Sirignano C.
    • Sirri G.
    • Stanco L.
    • Suur-Uski A.S.
    • Tauber J.A.
    • Tenti M.
    • Toffolatti L.
    • Tomasi M.
    • Tristram M.
    • Trombetti T.
    • Valiviita J.
    • Vansyngel F.
    • van Tent F.
    • Vielva P.
    • Wandelt B.D.
    • Wehus I.K.
    • Zacchei A.
    • Zonca A.
    Astron.Astrophys., 2017, 599, pp.A51. The characterization of the Galactic foregrounds has been shown to be the main obstacle in thechallenging quest to detect primordial B-modes in the polarized microwave sky. We make use of the Planck-HFI 2015 data release at high frequencies to place new constraints on the properties of the polarized thermal dust emission at high Galactic latitudes. Here, we specifically study the spatial variability of the dust polarized spectral energy distribution (SED), and its potential impact on the determination of the tensor-to-scalar ratio, r. We use the correlation ratio of the CBBℓ angular power spectra between the 217 and 353 GHz channels as a tracer of these potential variations, computed on different high Galactic latitude regions, ranging from 80% to 20% of the sky. The new insight from Planck data is a departure of the correlation ratio from unity that cannot be attributed to a spurious decorrelation due to the cosmic microwave background, instrumental noise, or instrumental systematics. The effect is marginally detected on each region, but the statistical combination of all the regions gives more than 99% confidence for this variation in polarized dust properties. In addition, we show that the decorrelation increases when there is a decrease in the mean column density of the region of the sky being considered, and we propose a simple power-law empirical model for this dependence, which matches what is seen in the Planck data. We explore the effect that this measured decorrelation has on simulations of the BICEP2-Keck Array/Planck analysis and show that the 2015 constraints from these data still allow a decorrelation between the dust at 150 and 353 GHz that is compatible with our measured value. Finally, using simplified models, we show that either spatial variation of the dust SED or of the dust polarization angle are able to produce decorrelations between 217 and 353 GHz data similar to the values we observe in the data. Key words: cosmic background radiation / cosmology: observations / submillimeter: ISM / dust, extinction⋆ Corresponding author: L. Montier, e-mail: Ludovic.Montier@irap.omp.eu; J. Aumont, e-mail: jonathan.aumont@ias.u-psud.fr (10.1051/0004-6361/201629164)
    DOI : 10.1051/0004-6361/201629164
  • Cournot-Nash Equilibria for Bandwidth Allocation under Base-Station Cooperation
    • Gomez J S
    • Vergne A
    • Martins P
    • Decreusefond Laurent
    • Chen Wei
    , 2017. —In this paper, a novel resource allocation scheme based on discrete Cournot-Nash equilibria and optimal transport theory is proposed. The originality of this framework lies in the joint optimization of downlink bandwidth allocation and cooperation between base stations. A tractable formalization is given in the form of a quadratic optimization problem. A low complexity approximate solution is derived and theoretically characterized. Simulations highlight the existence of an optimal working point, that maximizes user satisfaction ratio and network load. The impact of the network deployment on the optimum is numerically investigated, thanks to the β-Ginibre model. Indeed, base stations are assumed to be drawn according to β-Ginibre point processes. Numerical analysis shows that the network performance increases with β going to one.
  • Bravo monsieur Le Monde !
    • Zayana Karim
    Bulletion de l'APMEP, 2017. Mesurer la circonférence terrestre sans tourner en rond : Ce texte reprend un exposé donné le 10 mars 2017 au lycée Jean Zay à Paris, dans le cadre du plan national de formation « Construction des croisements didactiques en mathématiques et physique-chimie au collège
  • Quantitative analysis of normal and pathologic adrenal glands with 18F-FDOPA PET/CT
    • Moreau Aurélie
    • Giraudet Anne
    • Kryza David
    • Borson-Chazot Françoise
    • Bournaud Claire
    • Mognetti Thomas
    • Lifante Jean-Christophe
    • Combemale Patrick
    • Giammarile Francesco
    • Houzard Claire
    Nuclear Medicine Communications, Lippincott, Williams & Wilkins, 2017, 38 (9), pp.771-779. (10.1097/MNM.0000000000000708)
    DOI : 10.1097/MNM.0000000000000708
  • How to Find the Best Rated Items on a Likert Scale and How Many Ratings Are Enough
    • Liu Qing
    • Basu Debabrota
    • Goel Shruti
    • Abdessalem Talel
    • Bressan Stéphane
    , 2017, pp.351-359. (10.1007/978-3-319-64471-4_28)
    DOI : 10.1007/978-3-319-64471-4_28
  • Discovery and Registration: Finding and Integrating Components into Dynamic Systems
    • Rodriguez Berha Helena
    • Moissinac Jean-Claude Jc
    , 2017, pp.325-349. One of the major gaps in the current HTML5 web platform is the lack of an interoperable means for a multimodal application to discover services and applications available in a given space and network, for example, in a smart house with a network of connected objects. To address this gap, the Multimodal Interaction Working Group has produced a draft specification based on distributed services, which aims to support the Discovery and Registration of multimodal components. In this approach, the components are described and virtualized in a Resources Manager communicating bidirectionally through dedicated events. To facilitate the fine-grained management of concurrent multimodal interactions, the Resources Manager registers the distributed components and provides to the Interaction Manager the means to control them. In this way, interoperable search, discovery, and selection of heterogeneous and dynamic features on the Web of Things can be performed by multimodal applications producing natural interaction and a semantically rich user experience. (10.1007/978-3-319-42816-1_15)
    DOI : 10.1007/978-3-319-42816-1_15
  • Non-interference and local correctness in transactional memory
    • Kuznetsov Petr
    • Peri Sathya
    Theor. Comput. Sci., 2017, 688, pp.103-116. (10.1016/j.tcs.2016.06.021)
    DOI : 10.1016/j.tcs.2016.06.021
  • The notion of self-aware computing
    • Kounev Samuel
    • Lewis Peter
    • Bellman Kirstie
    • Bencomo Nelly
    • Camara Javier
    • Diaconescu Ada
    • Esterle Lukas
    • Geihs Kurt
    • Giese Holger
    • Gotz Sebastian
    • Inverardi Paola
    • Kephart Jeff
    • Zisman Andrea
    , 2017, pp.3-16.
  • Brain lesion detection in 3D PET images using max-trees and a new spatial context criterion
    • Urien Hélène
    • Buvat Irène
    • Rougon N. F.
    • Soussan Michael
    • Bloch Isabelle
    , 2017, LNCS 10225, pp.455-466. In this work, we propose a new criterion based on spatial context to select relevant nodes in a max-tree representation of an image, dedicated to the detection of 3D brain tumors for \textsuperscript{18}$F$-FDG PET images. This criterion prevents the detected lesions from merging with surrounding physiological radiotracer uptake. A complete detection method based on this criterion is proposed, and was evaluated on five patients with brain metastases and tuberculosis, and quantitatively assessed using the true positive rates and positive predictive values. The experimental results show that the method detects all the lesions in the PET.
  • Similarity and Contrast on Conceptual Spaces for Pertinent Description Generation
    • Sileno Giovanni
    • Bloch Isabelle
    • Atif Jamal
    • Dessalles Jean-Louis
    , 2017, LNAI 10505, pp.262-275. Within the general objective of conceiving a cognitive architecture for image interpretation able to generate outputs relevant to several target user profiles, the paper elaborates on a set of operations that should be provided by a cognitive space to guarantee the generation of relevant descriptions. First, it attempts to define a working definition of contrast operation. Then, revisiting well-known results in cognitive studies, it sketches a definition of similarity based on contrast, distin- guished from the metric defined on the conceptual space.
  • Détection et segmentation de tumeurs cérébrales en imagerie hybride TEP-IRM
    • Urien Hélène
    • Buvat Irène
    • Rougon N. F.
    • Soussan Michael
    • Bloch Isabelle
    , 2017, pp.50.
  • A Minimax Optimal Algorithm for Crowdsourcing
    • Bonald Thomas
    • Combes Richard
    , 2017. We consider the problem of accurately estimating the reliability of workers based on noisy labels they provide, which is a fundamental question in crowdsourcing. We propose a novel lower bound on the minimax estimation error which applies to any estimation procedure. We further propose Triangular Estimation (TE), an algorithm for estimating the reliability of workers. TE has low complexity, may be implemented in a streaming setting when labels are provided by workers in real time, and does not rely on an iterative procedure. We prove that TE is minimax optimal and matches our lower bound. We conclude by assessing the performance of TE and other state-of-the-art algorithms on both synthetic and real-world data.
  • On the uncontended complexity of anonymous agreement
    • Capdevielle Claire
    • Johnen Colette
    • Kuznetsov Petr
    • Milani Alessia
    Distributed Computing, 2017, 30 (6), pp.459-468. (10.1007/s00446-017-0297-z)
    DOI : 10.1007/s00446-017-0297-z
  • A Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
    • Haidar Batoul
    • Chamoun Maroun
    • Serhrouchni Ahmed
    Advances in Science, Technology and Engineering Systems Journal, Advances in Science Technology and Engineering Systems Journal (ASTESJ), 2017, 2 (6), pp.275-284. (10.25046/aj020634)
    DOI : 10.25046/aj020634
  • Non-Local Patch-Based Image Inpainting
    • Newson Alasdair
    • Almansa Andrés
    • Gousseau Yann
    • Pérez Patrick
    Image Processing On Line, IPOL - Image Processing on Line, 2017, 7, pp.373-385. Image inpainting is the process of filling in missing regions in an image in a plausible way. In this contribution, we propose and describe an implementation of a patch-based image inpainting algorithm. The method is actually a two-dimensional version of our video inpainting algorithm proposed in [A. Newson et al., Video inpainting of complex scenes, SIAM Journal of Imaging Sciences, 7 (2014)]. The algorithm attempts to minimize a highly non-convex functional, first introducted by Wexler et al. in [Wexler et al., Space-time video completion, CCVPR (2004)]. The functional specifies that a good solution to the inpainting problem should be an image where each patch is very similar to its nearest neighbor in the unoccluded area. Iterations are performed in a multi-scale framework which yields globally coherent results. In this manner two of the major goals of image inpainting, the correct reconstruction of textures and structures, are addressed. We address a series of important practical issues which arise when using such an approach. In particular, we reduce execution times by using the PatchMatch [C. Barnes, PatchMatch: a randomized correspondence algorithm for structural image editing, ACM Transactions on Graphics, (2009)] algorithm for nearest neighbor searches, and we propose a modified patch distance which improves the comparison of textured patches. We address the crucial issue of initialization and the choice of the number of pyramid levels, two points which are rarely discussed in such approaches. We provide several examples which illustrate the advantages of our algorithm, and compare our results with those of state-of-the-art methods. (10.5201/ipol.2017.189)
    DOI : 10.5201/ipol.2017.189
  • Déborder l'expérience pour laisser une trace. Vidéophénoménographie d'un rappeur
    • Kneubühler Marine
    , 2017, pp.147-242.