Alexandre BENOIT

Professor, Polytech Annecy-Chambéry.


Email : alexandre.benoit –@–

Phone : +33(0) 4 50 09 65 22 – télécopie : +33(0) 4 50 09 65 22

Office :  A223

Postal address : LISTIC – Polytech Annecy Chambéry, BP 80439, 74944 Annecy le Vieux Cedex, France

Position / responsabilities.

  • Permanent LISTIC Lab. member, professor position
  • Main teaching activities at Polytech Annecy Chambéry, Université Savoie Mont Blanc.

Research interests.

    Member of the “Apprentissage, Fusion et Télédétection (AFuTé) thematic” with strong connexions with ReGaRD thematics on distributed systems, HPC, data and ethics,

  • Image, video and more generally data understanding : from data preprocessing, features extraction to concept recognition (objects, action, etc.)  to classical 1D sensors.
  • Heterogeneous Data Fusion : associating multimodal inputs, images, contextual indicators, and others to make the decision process more reliable.
  • Sensor time series in general, from image sequences (multimedia, satellite remote sensing, astrophysics imaging) to classical sensors analysis.
  • Current methodological approaches rely on deep learning methods with some specific directions:
    • Frugal models, low computational cost by design: light architectures efficient in terms of training efficacy as well as reduced inference time.
    • Explainable models, with two approaches:
      • physical aware models design : by introducing physical knowledge in the model structure or by introducing optimization criteria related to the physical phenomenon to be considered.
      • developing XAI visualization techniques to help explain and understand model behaviors and predictions.
    • Physically informed models, ongoing activity
    • Federated learning, distributed and privacy preserving machine learning, ongoing activity.

Research Projects

  • A brief overview on these slides
  • Current projects:
    • Oil slicks detection and classification.
      • Keywords : deep Learning, SAR data analysis, heterogeneous data fusion, anomaly detection, semantic segmentation, classification.
      • Industrial partner : Total
    • Gamma rays classification and parameters estimation.
      • Keywords : deep Learning, astrophysics, stereoscopy, classification, regression.
      • Academic partner: LAPP
      • Industrial partner : Orobix

Teaching :

  • Related to my research activities:
    • Image and data processing with tools such as Matlab, and Python, OpenCV
    • Deep larning with Tensorflow.
    • Target students : PhD, Master and Bachelor degree and employed engineers.
  • General teaching activities:
    • Programming : scripting and object programming with C/C++/Java/Python/PHP, and others.
    • Modeling (UML, etc.)
  • Experience highlights :
    • image processing and machine learning to PhD students and Master 2 at University Savoie Mont Blanc.
    • machine learning at ESEN engineering school at Tunis (Tunisia)
    • machine learning at Renault compagny (Paris, Versailles)

Consulting :

  • Introducing machine learning in digital processes in the industry.
  • Data pre-processing, features extraction and decision making for classification, regression and other tasks for image, video and time series understanding.
  • Experience highlights :
    • Machine Learning and Deep Learning at Renault (Paris, Versailles)
    • Deep Learning at Total company(Paris)
    • Machine Learning at AboutGoods Company and Inventhys (Annecy)
    • Machine Learning with startups (Heliocity, Skiply and so on) along implications into the IDEFICS project

PhD thesis co-supervising :

Current PhDs:

  • 2018-2021 Emna Amri
    Topic : Automatic Oil Slicks detection and classification from Remote Sensing imaging using Deep Learning.
    Funding : Total company.
  • 2017-2020 Michael Dell’Aiera
    Topic : Semi supervised Deep neural networks for gamma rays analysis.
    Funding : H2020 ESCAPE project and LAPP lab collaboration.

Defended PhDs:

  • 2017-2020 Mickael Jacquemont
    Topic : Deep neural networks for the 3D analysis of gamma rays.
    Funding : H2020 ASTERICS project and the USMB fondation.
  • 2015-2019 Amina Ben Hamida
    Topic : Indexing of large Remote sensing images.
    Funding : French research ministry.
  • 2014-2019 Rizlène Raoui
    Topic : Automatic Sales receipt understanding using Deep Learing.
    Funding : CIFRE with AboutGoods Compagny.
  • 2013-2016 Nicolas Voiron
    Topic : Automating clustering of multimedia data bases for exploration.
    Funding : USMB
  • 2010-2013 Sabin Tiberius Strat
    Topic : Automating understanding of image sequences using a collaborative approach
    Funding : French research ministry

Conference/Workshop organization

  • 2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, July 22-24, 2015 Annecy, France
  • 2012 10th Workshop on Content-Based Multimedia Indexing (CBMI2012), 27-29 juin 2012, Annecy le Vieux, France.
  • 2011 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2011) July 18-22, 2011, jointly with Les Rencontres Francophones sur la Logique Floue et ses Applications (LFA 2011, aka French Days on Fuzzy Logic and Applications) in Aix-les-Bains, France.

Reading committee


IEEE Transactions on Image Processing ; Elsevier Computer Vision and Image Understanding ; Elsevier Signal Processing :Image Communication ; Multimedia Tools and APplications (MTAP) ; International Journal of Neural Systems ; MDPI Open Access Journal – Remote Sensing ; Hindawi – JournalOfRobotics ; ISPRS Journal of Photogrammetry and Remote Sensing ; JSTARS – GRSS | IEEE | Geoscience & Remote Sensing Society ; Integrated Computer-Aided Engineering


Main ones : IEEE International Conference on Image Processing ; International Workshop on Content-Based Multimedia Indexing ; JURSE – Joint Urban Remote Sensing Event ;  

Scientific animation

2018 – 2019 co coordination of the MAIM at GDR ISIS.
2015 – 2017 co coordination of the IRIM at GDR ISIS..

Codes :

Personal pages.

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