Alexandre BENOIT

Professor, Polytech Annecy-Chambéry.

Contact.

Email : alexandre.benoit –@– univ-smb.fr

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

Journals:

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

Conferences:

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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