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Dec 09, 2013 at 02:46 PM
Romain Raveaux: In 2006, he obtained two M.Sc., one in networking and telecommunication and another one in computer sciences from the University of Rouen (France). From 2006 to 2010, he had worked on his Ph.D. Thesis at the L3I laboratory of the University of La Rochelle. In 2019, he received the habilitation to be director of PhD thesis (HDR) from the University of Tours. Since 2011, he is an Associate Professor at the computer sciences lab LIFAT of the University of Tours. His work concerns the structural pattern recognition, proposing contributions related respectively to supervised graph classification and graph matching. Especially, a focus is given on similarity and dissimilarity computation on graphs. His work is applied to image analysis problems for object recognition and detection as well as molecule classification (Chemoinformatics). His scientific course is at the confluence of two research areas: combinatorial optimization and machine learning. Results and contributions of its research works have already been published in the forms of 3 theses and more than 40 research papers including 15 International Journals and 25 International conferences and workshops. Along his research activities, he has built strong collaboration with other research laboratories/universities at national and international levels. Accordingly, he has an active collaboration with 3 national laboratories/universities in France and one international collaboration with an Australian laboratory. As a lecturer, teaching assistant and associate professor, he has conducted teaching at different universities and institutions. He was a lecturer for the International Master of Research in Computer Science: Computer Aided and Decision Support at the University of Tours.
  • Computer vision
  • Machine Learning
  • Structural Pattern Recognition
  • Graph matching
  • Graph neural network
  • Discrete optimization
  • Reinforcement learning / Transfert learning

My work in three presentations :
  • Graph matching and classification from combinatorial optimization and machine learning viewpoints. PDF
  • Biodiversity estimation trough insect image classification. PDF
  • Document image quality assessment. PDF

I – Research Activity

I am a researcher at the Computer Science laboratory of Tours (LIFAT).

A – Center of Interest

  • Computer Vision (Detection, Recognition, Tracking)
  • Machine learning (Learning theory, Mathematical modelling, Graph neural network, Reinforcement learning)
  • Discrete optimization (Mathematical programming, Branch and bound, Matheuristics)

B - Research projects (en 2 topics)

Topic : Environnement

  • CARAMBA project (Regional project 2016-2019) : Entomology has had many applications in many biological domains (i.e insect counting as a biodiversity index). To meet a growing biological demand and to compensate a decreasing workforce amount, automated entomology has been around for decades. This challenge has been tackled by computer scientists as well as by biologists themselves. Views are adopted on image capture, feature extraction, classification methods and the tested datasets. Tasks: Image capture, Image recognition Publications : 2 journal papers and 2 conference papers.
    Poster in French and Presentation in English : Effective Training of Convolutional Neural Networks for Insect Image Recognition
  • Topic: Digital humanities and documents

    • VISIT project : In 2019, I was involved in setting up a research project of regional interest called VISIT. This project has been accepted. A post-doc will work for a year and a half on the development of an incremental algorithm for recognizing and indexing geo-localized images. In collaboration with the castle of Loche .
    • DOD project : in 2014-2015, I was in charge with Donatello Conte (LIFAT) of a work package named Document Image Quality Assessment of a project called Document Image Compression in relation with ITSOFT company. Short presentation Publication : 2 journal papers and 2 conference papers.
    • ALPAGE: From 2006 to 2010, the framework of my thesis was part of the ALPAGE project. Diachronic AnaLyse of Urban Space PArisian: GEomatic approach: ALPAGE is a research program, initiated in 2006, thanks to the support of the National Research Agency. Based on the association of 4 laboratories, and the collaboration of many other partners (Historian, Geomatics, …).

    Keynote Talks

    • Supervised Machine Learning for structured input/output: (2019). Polytech, Tours
      • 1. Introduction to supervised Machine Learning: A probabilistic viewpointPDF
      • 2. Connecting local models : The case of chains PDF slides
      • 3. Connecting local models : Beyond chains and trees.PDF slides
      • 4. Machine Learning and Graphs : Introduction and problems PDF slides
      • 7. Appendix : An introduction to deep learning. PDF slides
  • What AI for structural data ? (2018). CasciModot Federation, Orléans PDF
  • Parallel graph graph matching (2016). GREYC Caen. PDF
  • Estimating quality of documents (2015). ITESOFT Aimargues. PDF
  • From graph matching problem to Assignment problem : Application to Content-Based Image Retrieval. PDF
  • Keynote at the LINA lab (Nantes). Fouille et classification de graphes : Application à l'analyse d'image cadastrale. PDF
  • Keynote at the LABRI lab (Bordeaux). Fouille et classification de graphes : Application à l'analyse d'image cadastrale. PDF

Phd Students

  • Zeina Abu-Aishe (2012-2016) : Title : Anytime and Distributed Approaches for Graph Matching was supervised by Dr. Romain Raveaux, Prof. Jean-Yves Ramel and Prof. Patrick Martineau. Thesis report is available here
Last Updated ( Apr 09, 2020 at 04:51 PM )