Abdourrahmane Mahamane Atto
Publications
Publications
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Information spatiale de Lehmer et activation paramétrique pour la classification frugale de données positivesGRETSI, XXXe Colloque Francophone de Traitement du Signal et des Images, GRETSI, Aug 2025, Strabourg, France |
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MULTISCALE CORRELATION REGRESSION FOR JOINT CHANGE DETECTION AND CLASSIFICATION IN SAR TIME SERIESInternational Geoscience and Remote Sensing Symposium (IGARSS 2025), Aug 2025, Brisbane (AU), Australia |
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Un nouveau jeu de données pour la détection d'instabilités gravitaires dans les Alpes à partir d'interférogrammes SAR6e symposium MDIS - FormaTerre, Nov 2024, Orléans, France |
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DEM-assisted neural network for SAR-to-optical image translationIGARSS 2024 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2024, Athènes, Greece. pp.7649-7652, ⟨10.1109/IGARSS53475.2024.10641788⟩ |
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RENYI DIVERGENCES LEARNING FOR EXPLAINABLE CLASSIFICATION OF SAR IMAGE PAIRSICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2024, Seoul, South Korea. pp.7445-7449, ⟨10.1109/ICASSP48485.2024.10448227⟩ |
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Impact de la stratégie de décodage sur la traduction de modalité radar-optique d'images de télédétectionGRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, GRETSI - Groupe de Recherche en Traitement du Signal et des Images, Aug 2023, Grenoble, France. pp.929-932 |
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Apprentissage explicable d’un ensemble de divergences pour la similarité inter-classe de données SARGRETSI, XXIXème Colloque Francophone de Traitement du Signal et des Images, GRETSI, Aug 2023, Grenoble, France |
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Temporal Evolution of X and C Band SAR Backscattering in theMont-Blanc MassifInternational Geoscience and Remote Sensing Symposium (IGARSS 2023), Jul 2023, Pasadena, CA, United States |
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CNN Classification of Wet Snow By Physical Snowpack Model LabelingInternational Geoscience and Remote Sensing Symposium (IGARSS 2023), Jul 2023, Pasadena, CA, United States. ⟨10.1109/IGARSS52108.2023.10281833⟩ |
DEEP SEMANTIC FUSION OF SENTINEL-1 AND SENTINEL-2 SNOW PRODUCTS FOR SNOW MONITORING IN MOUNTAINOUS REGIONSIEEE International Geoscience and Remote Sensing Symposium 2023 (IGARSS 2023), Jul 2023, Pasadena (California), United States. ⟨10.1109/IGARSS52108.2023.10282065⟩ |
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Deep Learning of Radiometrical and Geometrical Sar Distorsions for Image Modality translationsICIP 2022 - 29th IEEE International Conference on Image Processing (IEEE ICIP), Oct 2022, Bordeaux, France. pp.1766-1770, ⟨10.1109/ICIP46576.2022.9897713⟩ |
Contribution of Artificial Intelligence models for the management of rockfall risks5th RSS Rock Slope Stability Symposium, Nov 2021, Chambéry, France |
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A Geometrical Wavelet Framework for the Time-Series Analysis of Full-Polarimetric Features2020 IEEE Radar Conference (RadarConf20), Sep 2020, Florence, Italy. pp.1-6, ⟨10.1109/RadarConf2043947.2020.9266403⟩ |
Transformation possibiliste de lois de probabilités elliptiquesRencontres francophones sur la logique floue et ses applications LFA 2019, Nov 2019, Alès, France |
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Geometric Multi-Wavelet Total Variation for SAR Image Time Series AnalysisInternational Conference on Information Fusion (FUSION 2018), Jul 2018, Ccambridge, United Kingdom |
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Robust Detection and Estimation of Change-Points in a Time Series of Multivariate ImagesEUSIPCO 2018, EURASIP, Sep 2018, Rome, Italy. ⟨10.23919/eusipco.2018.8553285⟩ |
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Multivariate Linear Time-Frequency modeling and adaptive robust target detection in highly textured monovariate SAR image2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017) , Mar 2017, Nouvelle-Orléans, United States. pp.4029 - 4033, ⟨10.1109/ICASSP.2017.7952913⟩ |
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Inverse Formulation of Temporal Closure and Proposed Solutions for Offset Tracking of Natural ScenesMultiTemp 2017, Jun 2017, Bruges, Belgium |
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Traitement automatique de "time lapse" : application à la surveillance de glaciers alpinsORASIS 2017, GREYC, Jun 2017, Colleville-sur-Mer, France |
Image Change Detection by Possibility Distribution DissemblanceFUZZ-IEEE 2017 : IEEE International Conference on Fuzzy Systems, Jul 2017, Naples, Italy. ⟨10.1109/FUZZ-IEEE.2017.8015641⟩ |
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Détection de changement sur images SAR monovariées par analyse temps-fréquence linéaireGRETSI 2017, Sep 2017, Juan-Les-Pins, France |
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Comparaison de Transformations Probabilité-Possibilité aux Moyens de Mesures de Dissemblance dans un Contexte de Détection de ChangementsLFA : Rencontres francophones sur la Logique Floue et ses Applications, Oct 2017, Amiens, France |
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Estimateur de Tyler régularisé dans le cas sous-déterminé. Application à la détection d'objets enfouisGRETSI 2017, Sep 2017, Juan Les Pins, France |
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A subspace approach for shrinkage parameter selection in undersampled configuration for Regularised Tyler EstimatorsICASSP 2017, Sep 2017, New Orleans, United States. pp.3291 - 3295, ⟨10.1109/ICASSP.2017.7952765⟩ |
Wavelet statistical analysis in multitemporal SAR imagesInternational Workshop on Statistical Modelling (IWSM), Jul 2016, Rennes, France |
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Multivariate statistical modeling for multi-temporal SAR change detection using wavelet transforms8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), 2015, Jul 2015, Annecy, France. pp.1-4, ⟨10.1109/Multi-Temp.2015.7245810⟩ |
Change analysis using multitemporal Sentinel-1 SAR imagesIEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015, Jul 2015, Milan, Italy |
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Change analysis of dual polarimetric Sentinel-1 SAR image time series using stationary wavelet transform and change detection matrixIEEE 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MULTITEMP), 2015, Jul 2015, Annecy, France |
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ARFBF MODEL FOR NON STATIONARY RANDOM FIELDS AND APPLICATION IN HRTEM IMAGESIEEE International Conference on Image Processing (ICIP) 2015, Sep 2015, Québec City, Canada |
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Convolution mixture of FBF and modulated FBF and application to HRTEM imagesGretsi 2015, Sep 2015, Lyon, France |
Non-stationary texture synthesis from random field modelingIEEE International Conference on Image Processing (ICIP) 2014, Oct 2014, Paris, France. pp.1-5 |
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Uniformly most powerful detection for integrate and fire time encodingEuropean Signal Processing Conference (EUSIPCO), Sep 2014, Lisbon, Portugal |
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ADAPTIVE MULTITEMPORAL FILTERING OF POLARIMETRIC SAR IMAGESIEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2014, Jul 2014, Québec, Canada. ⟨10.1109/IGARSS.2014.6947507⟩ |
Simulation of Image Time Series from Dynamical Fractional Brownian FieldsIEEE International Conference on Image Processing (ICIP), Oct 2014, Paris, France. pp.6086-6090, ⟨10.1109/ICIP.2014.7026228⟩ |
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SCHATTEN MATRIX NORM BASED POLARIMETRIC SAR DATA REGULARIZATION. APPLICATION OVER CHAMONIX MONT-BLANCInternational Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, POLinSAR 2013, Jan 2013, Frascati, Italy. 7 p |
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TEMPORAL ADAPTIVE FILTERING OF SAR IMAGE TIME SERIES BASED ON THE DETECTION OF STABLE AND CHANGE AREAS5th TerraSAR-X / 4th TanDEM-X Science Team Meeting - 2013, Jun 2013, Oberpfaffenhofen, Germany. 4 p |
Matrice de Divergences Multi-Temporelles et Analyse des Séries Chronologiques d'Images SARGDR-ISIS - Journée "Techniques et algorithmes pour les séries d'images multi-temporelles", Jun 2012, France |
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VECTOR AND MATRIX LP NORMS IN POLARIMETRIC RADAR FILTERINGIEEE International Geoscience and Remote Sensing Symposium, Jul 2012, Munich, Germany |
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Sparseness-based non-parametric detection and estimation of random signals in noiseSpars, Jun 2011, Edimbourg, United Kingdom |
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Sparsity Measure and the Detection of Significant DataSPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Inria Rennes - Bretagne Atlantique, Apr 2009, Saint Malo, France |
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Supervision of an industrial plant subject to a maximal duration constraint9th International Workshop on Discrete Event Systems, May 2008, Göteborg, Sweden. pp.254-259 |
Utilisation des séries temporelles d’images Sentinel-1 pour l’observation des glaciers des AlpesPNTS 2018, Mar 2018, Grenoble, France |
Change Detection and Image Time Series Analysis 2Wiley, 1, 2021, ⟨10.1002/9781119882299⟩ |
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Fractional Field Image Time Series Modeling and Application to Cyclone TrackingWiley, 1, 2021, ⟨10.1002/9781119882268.ch6⟩ |
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Thresholds and Distances to Better Detect Wet Snow over Mountains with Sentinel-1 Image Time SeriesWiley, 1, 2021, ⟨10.1002/9781119882268.ch5⟩ |
Change Detection and Image Time Series Analysis 1Wiley, 1, 2021, ⟨10.1002/9781119882268⟩ |
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Multiclass Multilabel Change of State Transfer Learning from Image Time SeriesWiley, 1, 2021, ⟨10.1002/9781119882299.ch6⟩ |
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Unsupervised Functional Information Clustering in Extreme Environments from Filter Banks and Relative EntropyWiley, 1, 2021, ⟨10.1002/9781119882268.ch4⟩ |
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Ondelettes et Processus StochastiquesLavoisier-Hermès. 297 p., 2017, 978-2-7462-4800-7 |
Chapter 6: Multiclass Multilabel Change of State Transfer Learning from Image Time SeriesChange Detection and Image Time Series Analysis 2: Supervised Methods, 1, pp.223-245, 2021, 9781119882299. ⟨10.1002/9781119882299.ch6⟩ |
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Thresholds and distances to better detect wet snow over mountains with Sentinel-1 image time seriesChange Detection and Image Time Series Analysis, 1: Unsupervised Methods, Wiley, pp.1-18, 2021, ⟨10.1002/9781119882268.ch5⟩ |
Wavelet shrinkage : from sparsity and robust testing to smooth adaptationFractals and Related Fields, Birkhauser, 2010 |
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Neural Transfer Function Library Deriving From Parametric Probability Signatures2023 |
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The Role of Parametrically Learnable Neural Transfer Functions in Artificial Intelligence2025 |
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Softlog-Softmax Layers and Divergences Contribute to a Computationally Dependable Ensemble Learning2025 |
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Fractional Order Stochastic Image Integration Models and Deep Learning of Multi-Fractional Interactions2017 |
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Wavelet Operators and Multiplicative Observation Models - Application to Change-Enhanced Regularization of SAR Image Time Series2016 |
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Analyse en Ondelettes et par Paquets d'Ondelettes de Processus Aléatoires Stationnaires, et Application à l'Estimation Non-ParamétriqueMathématiques [math]. Ecole Nationale Supérieure des Télécommunications de Bretagne - ENSTB; Université Rennes 1, 2008. Français. ⟨NNT : ⟩ |
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Analyse des Séquences de Processus et Champs Aléatoires d'OndelettesMathématiques [math]. Université Grenoble Alpes, 2015 |