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Dr Jonathan Weber, PhD in Computer Science

Associate Professor @ Université de Haute-Alsace

Lecturer @ ENSISA

Researcher @ IRIMAS

Keywords
  • Image processing
  • Mathematical morphology
  • Pattern Recognition
  • Data Science
  • Deep Learning
  • Time series classification

Latest news
April 2019 : Paper accepted in Artificial Intelligence Review !
April 2019 : Scientific stay at MH-Hannover to work with Prof. Friederich Feuerhake (DAAD Grant) March 2019 : Paper accepted at AIME 2019 !
March 2019 : Two papers accepted at IJCNN 2019 !
February 2019 : Start of Tsegamlak Terefe Debella PhD thesis
January 2019 : Paper accepted in Data Mining and Knowledge Discovery
November 2018 : Grant from DAAD obtained for a scientific stay at MH-Hannover !
October 2018 : Paper accepted at Big Data 2018 !
October 2018 : Start of Baptiste Lafabregue PhD thesis
August 2018 : Paper accepted in Artificial Intelligence in Medicine

Bio
Positions
Since 2016 Associate Professor Université de Haute-Alsace
2012-2016 Associate Professor Université de Lorraine
2011-2012 Teaching and Research Assistant Université de Lorraine
2010-2011 Teaching and Research Assistant Université de Strasbourg
2007-2010 R&D Engineer Ready Business System
Responsabilities
Since 2018 Co-Head of Master Computer Science and Mobility Faculty of Science and Technology, Mulhouse
Since 2017 Head of DU UHA 4.0.4 UHA 4.0
2013-2016 Head of Multimedia and Web Department Saint-Dié Institute of Technology
Education
2011 PhD in Computer Science Université de Strasbourg
2007 MSc in Computer Science Université de Strasbourg
Organising Committee Member
Association Member
Program Committee Member
Reviewer
Research
Research Projects
Name Type Date Involvment
TIMES ANR 2017-2020 Member
OPMoPS ANR/BMBF 2017-2020 Member
PLASIDIA AMI 2017-2018 Member
APIM PIR UHA 2017 Project Leader
Sys-MIFTA ERACoSysMed 2016-2019 Member
AMIS CHIST-ERA 2016-2019 Member
SYSIMIT BMBF 2015-2018 Member
ECOSGIL ANR-JC 2005-2008 Master Student
FoDoMuSt ACI 2004-2007 Master Student
(Co-)Supervised students/engineers
PhD student Date Subject
Tsegamlak Terefe Debella 2019 - ... Optimal computation of average time series
Baptiste Lafabregue 2018 - ... Constrained clustering of satellite image time series
Mounir Bendali-Braham 2017 - ... Crowd behaviour analysis
Hassan Ismail Fawaz 2017 - ... Mining medical data
Bastien Latard 2016 - ... Semantic Analys of scientific articles
Master Student Date Subject
Robin Heckenauer 2019 Deep Learning applied to histopathological slides
Hugo Besadoux 2018 Deep Learning applied to LIDAR data
Nirma Naruka 2018 Diaphragm segmentation in 3D imagery
Oleg Eremin 2017 Deep Learning applied to medical imagery
Rahul Sahal 2017 Overlaid text extraction in news video
Giovanni de Angelis 2016 People counting using 3D camera
Antonio Terrone 2016 People counting using depth image
Roberto Pisapia 2016 People counting using embedded systems
Julien Bidolet 2014 Graph indexing for image classification
Michał Kowalczyk 2012 Image segmentation on mobile environment
Jean-François Kraemer 2010 Video segmentation/annotation tool
Vincent Danner 2009 Optimized video management for Pelican
Engineer Date Subject
Paul Bourgeois 2018 - ....... Time series analysis of diabetic patient data
Software

Pelican

Pelican LogoPolyvalent Extensible Library for Image Computing and ANalysis is a multi-platform framework, written in Java, dedicated to Image Processing. The project started at the Université de Strasbourg in 2005 but its contributors are no longer in this university. It allows the processing of image from different types (2D, video, 3D, 3D+t) and origins (casual, medical, astronomic, remote sensing, ...) and contains many standard image processing algorithms.
Pelican contains more than 100k lines of code and is freely available under CC BY-NC 4.0 license.

Code Download (66.3M)

Coastal

CoastlineSoftware developped during the ANR-JC ECOSGIL project. Written in Java, it is a tool dedicated to geographers. It achieves several processing on coastal remote sensing images such as the extraction of coastline. It uses the Pelican framework. It is still used by geographers (initial release dated from 2007).

Download (21.9M)

TeSySp

Symbol spotting exampleTeSySp (Technical Symbol Spotter) was initially developed to demonstrate our work on symbol spotting in technical documents. Written in Java, it is based on Pelican framework. It is an improvment of our initial approach, in particular the use of machine learning techniques to filter false-positives result. Moreover, TeSySp will allow to create ground-truth for symbol spotting and will contain different metrics to evaluate the quality of spotting results.

Code Still under development
Teaching
Institutions and departments
Since 2017 Information and Communication Department Faculty of Economics, Socials and Law studies, Mulhouse
Since 2017 Computer Science for Business Department Faculty of Science and Technology, Mulhouse
Since 2016 Computer Science Department École Nationale Supérieure d'Ingénieurs Sud-Alsace
2011-2016 Multimedia and Web Department Saint-Dié Institute of Technology
2013-2016 Computer Science Department Ecole Nationale Supérieure des Mines de Nancy
2009-2011 Computer Science Department Robert Schuman Institute of Technology
2009 Physical Measurements Department Louis Paster Institute of Technology
Courses
  • Web (HTML, CSS, PHP, Javascript, ...)
  • Operating Systems
  • Programming (C, C#, Java, Python, ...)
  • Database (SQL, UML)
  • Logic
  • Semantic Web
  • Artificial Intelligence
  • Content Management System
  • Mobile programming (Android)
  • Video game programming (Unity)
  • Project Management
  • Collaborative Tools
  • Security
  • Computer Graphics
  • Image processing
  • Mathematical Morphology
  • Data compression
  • Networks
Contact
jonathan [dot] weber [at] uha [dot] fr
+33 03 89 33 69 76
ENSISA
12, rue des frères Lumière
68093 Mulhouse FRANCE
Publications
Research Articles in International Journals
  1. Vinh-Trung Luu, Germain Forestier, Jonathan Weber, Paul Bourgeois, Fahima Djelil and Pierre-Alain Muller,
    A review of alignment-based similarity measures for web usage mining,
    Artificial Intelligence Review, in press, 2019
  2. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Deep learning for time series classification: a review,
    Data Mining and Knowledge Discovery, in press, 2019
  3. Germain Forestier, François Petitjean, Pavel Senin, Fabien Despinoy, Arnaud Huaulmé, Hassan Ismail Fawaz, Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Muller and Pierre Jannin,
    Surgical motion analysis using discriminative interpretable patterns,
    Artificial Intelligence in Medicine, Vol. 99, pp. 3-11 (9 pages), September 2018
    DOI
  4. Manuel Grand-Brochier, Antoine Vacavant, Camille Kurtz, Jonathan Weber, Laure Tougne,
    Tree Leaves Extraction in Natural Images: Comparative Study of Preprocessing Tools and Segmentation Methods,
    IEEE Transactions on Image Processing, Vol. 24, No. 5, pp. 1549-1560 (12 pages), May 2015
    PDF DOI
  5. François Petitjean, Jonathan Weber,
    Efficient Satellite Image Time Series Analysis Under Time Warping,
    IEEE Geoscience Remote Sensing Letters, Vol. 11, No. 6, pp. 1143-1147 (5 pages), June 2014.
    PDF DOI
  6. Jonathan Weber, Sébastien Lefèvre,
    Fast Quasi-Flat Zones Filtering Using Area Threshold and Region Merging,
    Journal of Visual Communication and Image Representation, Vol. 24, No. 3, pp. 397-409 (13 pages), April 2013.
    PDF DOI
  7. Jonathan Weber, Sébastien Lefèvre,
    Spatial and Spectral Morphological Template Matching,
    Image and Vision Computing, Vol. 30, No. 12, pp. 934-945 (12 pages), December 2012.
    PDF DOI
Communications to International Conferences and Workshops
  1. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, François Petitjean, Lhassane Idoumghar and Pierre-Alain Muller,
    Automatic alignment of surgical videos using kinematic data,
    Conference on Artificial Intelligence in Medecine (AIME), (10 pages), Poznan, Poland, June 2019
  2. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Deep Neural Network Ensembles for Time Series Classification,
    IEEE International Joint Conference on Neural Networks (IJCNN), (6 pages), Budapest, Hungary, July 2019
  3. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Adversarial attacks on deep neural networks for time series classification,
    IEEE International Joint Conference on Neural Networks (IJCNN), (8 pages), Budapest, Hungary, July 2019
  4. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Transfer learning for time series classification,
    IEEE International Conference on Big Data, (8 pages), Seattle, USA, December 2018
  5. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Evaluating surgical skills from kinematic data using convolutional neural networks,
    Medical Image Computing and Computer Assisted Intervention (MICCAI), (8 pages), Granada, Spain, September 2018
  6. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Data augmentation using synthetic data for time series classification with deep residual networks,
    ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data, (8 pages), Dublin, Ireland, September 2018
  7. Bastien Latard, Jonathan Weber, Germain Forestier and Michel Hassenforder,
    Using Semantic Relations between Keywords to Categorize Articles from Scientific Literature,
    International Conference on Tools with Artificial Intelligence (ICTAI), (5 pages), Boston, USA, November 2017
  8. Bastien Latard, Jonathan Weber, Germain Forestier and Michel Hassenforder,
    Towards a Semantic Search Engine for Scientific Articles,
    International Conference on Theory and Practice of Digital Libraries (TPDL), (4 pages), Thessaloniki, Greece, September 2017
    DOI
  9. Rachida Es-Salhi, Imane Daoudi, Jonathan Weber, Hamid El Ouardi, Saida Tallal, Hicham Medromi,
    Multi-scale image co-segmentation,
    Advances in Ubiquitous Networking: Proceedings of the UNet'15, Springer Singapore, pp. 381-390 (10 pages), Casablanca, Morocco, September 2015
    DOI
  10. Erhan Aptoula, Jonathan Weber, Sébastien Lefèvre,
    Vectorial Quasi-flat Zones for Color Image Simplification,
    International Symposium on Mathematical Morphology (ISMM), Springer-Verlag Lecture Notes in Computer Science, Vol. 7883, pp. 231-242 (12 pages), Uppsala, Sweden, May 2013.
    PDF DOI SLIDES
  11. Jonathan Weber, Salvatore Tabbone,
    Symbol spotting for technical documents : An efficient template-Matching approach,
    International Conference on Pattern Recognition (ICPR), 4 pages, Tsukuba, Japan, November 2012.
    PDF URL POSTER
  12. Michal Kowalczyk, Bertrand Kerautret, Benoît Naegel, Jonathan Weber,
    Revisiting Component Tree Based Segmentation Using Meaningful Photometric Informations,
    International Conference on Computer Vision and Graphics (ICCVG), Springer-Verlag Lecture Notes in Computer Science, Vol. 7594, pp. 475-482 (8 pages), Warsaw, Poland, September 2012.
    PDF DOI POSTER
  13. Jonathan Weber, François Petitjean, Pierre Gançarski,
    Towards efficient satellite time series analysis: combination of Dynamic Time Warping and Quasi-Flat Zones,
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 4387-4390 (4 pages), Munchen, Germany, July 2012.
    PDF DOI POSTER
  14. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Interactive Video Segmentation based on Quasi-Flat Zones,
    International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 265-270 (6 pages), Dubrovnik, Croatia, September 2011.
    PDF URL SLIDES
  15. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Spatio-temporal quasi-flat zones for morphological video segmentation,
    International Symposium on Mathematical Morphology (ISMM), Springer-Verlag Lecture Notes in Computer Science, Vol. 6671, pp. 178-189 (12 pages), Intra, Italy, July 2011.
    PDF DOI POSTER
  16. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Video Object Mining : Issues and Perspectives,
    IEEE International Conference on Semantic Computing (ICSC), pp. 85-90 (6 pages), Pittsburgh, USA, September 2010.
    PDF URL SLIDES
  17. Jonathan Weber, Sébastien Lefèvre,
    A multivariate Hit-or-Miss transform for conjoint spatial and spectral template matching,
    IEEE International Conference on Image and Signal Processing (ICISP), Springer-Verlag Lecture Notes in Computer Sciences, Vol. 5099, pp. 226-235 (10 pages), Cherbourg, France, August 2008.
    PDF DOI SLIDES
  18. Anne Puissant, Sébastien Lefèvre, Jonathan Weber,
    Coastline extraction in VHR imagery using mathematical morphology with spatial and spectral knowledge,
    International Society for Photogrammetry and Remote Sensing Congress (ISPRS), 6 pages, Beijing, China, July 2008.
    PDF URL
  19. Sébastien Lefèvre, Jonathan Weber, David Sheeren,
    Automatic building extraction in VHR images using advanced morphological operators,
    IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (URBAN), 5 pages, Paris, France, April 2007.
    PDF DOI
Book Chapters
  1. Sébastien Lefèvre, Erhan Aptoula, Benjamin Perret, Jonathan Weber,
    Morphological Template Matching in Color Images,
    Advances in Low-Level Color Image Processing, Springer,pp. 241-277 (37 pages), 2013.
    DOI
Editorial Activities in french
  1. Julien Longhi, Jonathan Weber,
    La communication numérique, du code à l'information, L'Harmattan, 2018.
    DOI
Book Chapters in french
  1. Jonathan Weber,
    Enseigner l’informatique en DUT MMI : Difficultés et retours d’expérience,
    La communication numérique, du code à l'information, L'Harmattan,pp. 155-177 (23 pages), 2018.
    DOI
Research Articles in National Journals
  1. David Sheeren, Sébastien Lefèvre, Jonathan Weber,
    La morphologie mathématique binaire pour l'extraction automatique des bâtiments dans les images THRS,
    Revue Internationale de Géomatique, numéro thématique "Informations géographiques : structuration, extraction et utilisation", Vol. 17, No. 3-4, pp. 333-352 (20 pages), 2007.
    PDF DOI
Communications to National Conferences and Workshops
  1. Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar and Pierre-Alain Muller,
    Augmentation de données utilisant des données synthétiques pour la classification de séries temporelles par réseaux profonds résiduels,
    Journées Francophones Extraction et Gestion des Connaissances (EGC), 2 pages, Metz, France, January 2019.
  2. Bastien Latard, Jonathan Weber, Germain Forestier, Michel Hassenforder,
    Catégorisation d’articles scientifiques basée sur les relations sémantiques des mots-clés,
    Journées Francophones Extraction et Gestion des Connaissances (EGC), 2 pages, Paris, France, January 2018.
  3. Bastien Latard, Jonathan Weber, Germain Forestier, Michel Hassenforder,
    Utilisation des relations sémantiques des mots-clés pour la catégorisation d’articles scientifiques,
    Atelier Science des Données et Humanités Numériques (SDHN), Journées Francophones Extraction et Gestion des Connaissances (EGC), 12 pages, Paris, January 2018.
  4. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Segmentation vidéo interactive par zones quasi-plates,
    Colloque GRETSI sur le Traitement du Signal et des Images, 4 pages, Bordeaux, France, September 2011.
    PDF POSTER
  5. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Zones quasi-plates spatio-temporelles et segmentation morphologique de séquences vidéo,
    Congrès des jeunes chercheurs en vision par ordinateur (ORASIS), 8 pages, Praz-sur-arly, France, June 2011.
    PDF POSTER
  6. Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski,
    Fouille vidéo orientée objet, une approche générique,
    Atelier Fouille de données complexes, Journées Francophones Extraction et Gestion des Connaissances (EGC), pp. 9-20 (12 pages), Brest, France, January 2011.
    PDF SLIDES
  7. Jonathan Weber, Sébastien Lefèvre, David Sheeren,
    Détection des bâtiments dans les images THRS avec la morphologie mathématique,
    Colloque International de Géomatique et d'Analyse Spatiale (SAGEO), 5 pages, Strasbourg, France, September 2006.
    PDF
Dissertations
  1. Jonathan Weber,
    Segmentation morphologique interactive pour la fouille de séquences vidéo,
    PhD dissertation, 155 pages, Université de Strasbourg, France, September 2011.
    PDF SLIDES
  2. Jonathan Weber,
    Détection d’objets géographiques du littoral dans des images satellites multispectrales,
    Master dissertation, 60 pages, Université de Strasbourg, France, June 2007.
    PDF SLIDES
Other communications
  1. Jonathan Weber, Salvatore Tabbone,
    Localisation de symboles dans des documents techniques,
    Congrès National de la Recherche en IUT (CNRIUT), 1 page, Épinal, France, March 2015.
    PDF SLIDES
  2. Rachida Es-Salhi, Imane Daoudi, Hamid El Ouardi, Jonathan Weber,
    Co-segmentation des images : État de l’art,
    Journées Doctorales en Technologies de l’Information et de la Communication (JDTIC), Rabat, Morocco, March 2014
  3. Jonathan Weber, Sébastien Lefèvre, David Sheeren,
    Extraction automatique de bâtiments dans des images satellites THRS en utilisant des opérateurs de Morphologie Mathématique,
    Atelier du Programme de Télédétection Spatiale (PNTS), 1 page, Nantes, France, September 2007.
    PDF