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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 Communications par Fibres Optiques : La Fin de l'Age de Cuivre
    • Gallion Philippe
    , 2017, pp.8.
  • Décomposition de séries temporelles d'images SAR pour la détection de changements
    • Lobry Sylvain
    • Denis L.
    • Zhao Weiying
    • Tupin Florence
    Traitement du Signal, Lavoisier, 2017.
  • Robust Downbeat Tracking Using an Ensemble of Convolutional Networks
    • Durand Simon
    • Bello Juan Pablo
    • David Bertrand
    • Richard Gael
    IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (1), pp.76-89. <div><p>In this paper, we present a novel state of the art system for automatic downbeat tracking from music signals. The audio signal is first segmented in frames which are synchronized at the tatum level of the music. We then extract different kind of features based on harmony, melody, rhythm and bass content to feed convolutional neural networks that are adapted to take advantage of the characteristics of each feature. This ensemble of neural networks is combined to obtain one downbeat likelihood per tatum. The downbeat sequence is finally decoded with a flexible and efficient temporal model which takes advantage of the assumed metrical continuity of a song. We then perform an evaluation of our system on a large base of 9 datasets, compare its performance to 4 other published algorithms and obtain a significant increase of 16.8 percent points compared to the second best system, for altogether a moderate cost in test and training. The influence of each step of the method is studied to show its strengths and shortcomings.</p></div> (10.1109/TASLP.2016.2623565)
    DOI : 10.1109/TASLP.2016.2623565
  • Déborder l'expérience pour laisser une trace. Vidéophénoménographie d'un rappeur
    • Kneubühler Marine
    , 2017, pp.147-242.
  • On some bounds for symmetric tensor rank of multiplication in finite fields
    • Ballet Stéphane
    • Pieltant Julia
    • Rambaud Matthieu
    • Sijsling Jeroen
    , 2017, 686, pp.93 - 121. We establish new upper bounds about symmetric bilinear complexity in any extension of finite fields. Note that these bounds are not asymptotical but uniform. Moreover, we discuss the validity of certain published bounds. (10.1090/conm/686/13779)
    DOI : 10.1090/conm/686/13779
  • Conception d'absorbants à base de métasurfaces et Application de la Transformation d'Espace pour le contrôle du rayonnement d’une antenne imprimée
    • Lepage A. C.
    • Begaud Xavier
    , 2017.
  • LISP EID Block
    • Iannone Luigi
    • Lewis Darrel
    • Meyer Dave
    • Fuller Vince
    , 2017.
  • On perturbed proximal gradient algorithms
    • Atchadé Yves
    • Fort Gersende
    • Moulines Éric
    Journal of Machine Learning Research, Microtome Publishing, 2017, 18 (10), pp.1-33.
  • Dynamic mitigation of EDFA power excursions with machine learning
    • Huang Yishen
    • Gutterman Craig L.
    • Samadi Payman
    • Cho Patricia B.
    • Samoud Wiem
    • Ware Cédric
    • Lourdiane Mounia
    • Zussman Gil
    • Bergman Keren
    Optics Express, Optical Society of America - OSA Publishing, 2017, 25 (3), pp.2245 - 2258. Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. We also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm (10.1364/OE.25.002245)
    DOI : 10.1364/OE.25.002245
  • Formal Semantics of Behavior Specifications in the Architecture Analysis and Design Language Standard
    • Besnard Loic
    • Gautier Thierry
    • Le Guernic Paul
    • Guy Clément
    • Talpin Jean-Pierre
    • Larson Brian
    • Borde Etienne
    , 2017. (10.1007/978-981-10-4436-6_3)
    DOI : 10.1007/978-981-10-4436-6_3
  • Parameter estimation of perfusion models in dynamic contrast-enhanced imaging: a unified framework for model comparison
    • Romain Blandine
    • Rouet Laurence
    • Ohayon Daniel
    • Lucidarme Olivier
    • d'Alché-Buc Florence
    • Letort Véronique
    Medical Image Analysis, Elsevier, 2017, 35, pp.360--374. Patients follow-up in oncology is generally performed through the acquisition of dynamic sequences of contrast-enhanced images. Estimating parameters of appropriate models of contrast intake diffusion through tissues should help characterizing the tumour physiology. However, several models have been developed and no consensus exists on their clinical use. In this paper, we propose a unified framework to analyse models of perfusion and estimate their parameters in order to obtain reliable and relevant parametric images. After defining the biological context and the general form of perfusion models, we propose a methodological framework for model assessment in the context of parameter estimation from dynamic imaging data: global sensitivity analysis, structural and practical identifiability analysis, parameter estimation and model comparison. Then, we apply our methodology to five of the most widely used compartment models (Tofts model, extended Tofts model, two-compartment model, tissue-homogeneity model and distributed-parameters model) and illustrate the results by analysing the behaviour of these models when applied to data acquired on five patients with abdominal tumours. (10.1016/j.media.2016.07.008)
    DOI : 10.1016/j.media.2016.07.008
  • Demystifying the asymptotic behavior of global denoising
    • Houdard Antoine
    • Almansa Andrès
    • Delon Julie
    Journal of Mathematical Imaging and Vision, Springer Verlag, 2017. In this work, we revisit the global denoising framework recently introduced by Talebi and Milanfar. We analyze the asymptotic behavior of its mean-squared error restoration performance in the oracle case when the image size tends to infinity. We introduce precise conditions on both the image and the global filter to ensure and quantify this convergence. We also make a clear distinction between two different levels of oracle that are used in that framework. By reformulating global denoising with the classical formalism of diagonal estimation, we conclude that the second-level oracle can be avoided by using Donoho and Johnstone’s theorem, whereas the first-level oracle is mostly required in the sequel. We also discuss open issues concerning the most challenging aspect, namely the extension of these results to the case where neither oracle is required. (10.1007/s10851-017-0716-6)
    DOI : 10.1007/s10851-017-0716-6
  • Planck intermediate results. LI. Features in the cosmic microwave background temperature power spectrum and shifts in cosmological parameters
    • Aghanim N.
    • Akrami Yashar
    • Ashdown M.
    • Aumont J.
    • Ballardini M.
    • Banday A.J.
    • Barreiro R.B.
    • Bartolo N.
    • Basak S.
    • Benabed K.
    • Bersanelli M.
    • Bielewicz P.
    • Bonaldi A.
    • Bonavera L.
    • Bond J.R.
    • Borrill J.
    • Bouchet F.R.
    • Burigana C.
    • Calabrese E.
    • Cardoso J.F.
    • Challinor A.
    • Chiang H.C.
    • Colombo L.P.L.
    • Combet C.
    • Crill B.P.
    • Curto A.
    • Cuttaia F.
    • de Bernardis P.
    • de Rosa A.
    • de Zotti G.
    • Delabrouille J.
    • Di Valentino E.
    • Dickinson C.
    • Diego J.M.
    • Dore O.
    • Ducout A.
    • Dupac X.
    • Dusini S.
    • Efstathiou G.
    • Elsner F.
    • Ensslin T.A.
    • Eriksen H.K.
    • Fantaye Y.
    • Finelli F.
    • Forastieri F.
    • Frailis M.
    • Franceschi E.
    • Frolov A.
    • Galeotta S.
    • Galli S.
    • Ganga K.
    • Genova-Santos R.T.
    • Gerbino M.
    • Gonzalez-Nuevo J.
    • Gorski K.M.
    • Gruppuso A.
    • Gudmundsson J.E.
    • Herranz D.
    • Hivon E.
    • Huang Z.
    • Jaffe A.H.
    • Jones W.C.
    • Keihanen E.
    • Keskitalo R.
    • Kiiveri K.
    • Kim J.
    • Kisner T.S.
    • Knox L.
    • Krachmalnicoff N.
    • Kunz M.
    • Kurki-Suonio H.
    • Lagache G.
    • Lamarre J.M.
    • Lasenby A.
    • Lattanzi M.
    • Lawrence C.R.
    • Le Jeune M.
    • Levrier F.
    • Lewis A.
    • Lilje P.B.
    • Lilley M.
    • Lindholm V.
    • Lopez-Caniego M.
    • Lubin P.M.
    • Ma Y.Z.
    • 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.
    • Meinhold P.R.
    • Mennella A.
    • Migliaccio M.
    • Millea M.
    • Miville-Deschenes M.A.
    • Molinari D.
    • Moneti A.
    • Montier L.
    • Morgante G.
    • Moss A.
    • Narimani A.
    • Natoli P.
    • Oxborrow C.A.
    • Pagano L.
    • Paoletti D.
    • Patanchon G.
    • Patrizii L.
    • Pettorino V.
    • Piacentini F.
    • Polastri L.
    • Polenta G.
    • Puget J.L.
    • Rachen J.P.
    • Racine B.
    • Reinecke M.
    • Remazeilles M.
    • Renzi A.
    • 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.
    • Tavagnacco D.
    • Tenti M.
    • Toffolatti L.
    • Tomasi M.
    • Tristram M.
    • Trombetti T.
    • Valiviita J.
    • van Tent F.
    • Vielva P.
    • Villa Francesca
    • Vittorio N.
    • Wandelt B.D.
    • Wehus I.K.
    • White M.
    • Zacchei A.
    • Zonca A.
    Astronomy & Astrophysics - A&A, EDP Sciences, 2017, 607, pp.A95. The six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium τ, the baryon density ωb, the matter density ωm, the angular size of the sound horizon θ∗, the spectral index of the primordial power spectrum, ns, and Ase− 2τ (where As is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment ℓ < 800 in the Planck temperature power spectrum) and an all angular-scale data set (ℓ < 2500Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1σ expected dispersion for each parameter, are { Δτ,ΔAse− 2τ,Δns,Δωm,Δωb,Δθ∗ } = { −1.7,−2.2,1.2,−2.0,1.1,0.9 }, with a χ2 value of 8.0. We find that this χ2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing ℓ < 800 instead to ℓ> 800, or splitting at a different multipole, yields similar results. We examined the ℓ < 800 model residuals in the ℓ> 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is τ, which, at fixed Ase− 2τ, affects the ℓ> 800 temperature power spectrum solely through the associated change in As and the impact of that on the lensing potential power spectrum. We also ask, “what is it about the power spectrum at ℓ < 800 that leads to somewhat different best-fit parameters than come from the full ℓ range?” We find that if we discard the data at ℓ < 30, where there is a roughly 2σ downward fluctuation in power relative to the model that best fits the full ℓ range, the ℓ < 800 best-fit parameters shift significantly towards the ℓ < 2500 best-fit parameters. In contrast, including ℓ < 30, this previously noted “low-ℓ deficit” drives ns up and impacts parameters correlated with ns, such as ωm and H0. As expected, the ℓ < 30 data have a much greater impact on the ℓ < 800 best fit than on the ℓ < 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high-ℓ residuals and the deficit in low-ℓ power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between PlanckTT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.Key words: cosmology: observations / cosmic background radiation / cosmological parameters / cosmology: theory (10.1051/0004-6361/201629504)
    DOI : 10.1051/0004-6361/201629504
  • 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
  • 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
  • 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
  • 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.
  • 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.
  • 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.
  • 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
  • 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
  • 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
  • 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.
  • 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
  • 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.