Guillaume Noyel
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guillaume-noyel
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0000-0002-7374-548X
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136317006
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noyel_g_1
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215158650
- ISNI : 0000000359301273
- ResearcherID : P-5930-2016
Présentation
Guillaume Noyel was born in France, and obtained a MSc in Image Processing from CPE-Lyon and a MSc in Computer Vision from Jean Monnet University, Saint-Etienne, France. He received his PhD in Mathematical Morphology from Mines ParisTech, Paris, in 2008 before working as a researcher in image processing and machine learning at the Michelin Research Centre for 6 years. Dr. Noyel joined IPRI in 2014 as a Research Director where he created a new scientific axis in medical image analysis. He was awarded a European grant from the European Union. The University of Strathclyde, Glasgow, United Kingdom invited him as a Visiting Researcher in the Department of Mathematics and Statistics. In 2021, the University of Reims Champagne-Ardenne, France, has awarded him his accreditation to supervise research (Habilitation) in the field of Computer Vision. He also joined Télécom Saint-Etienne and Hubert Curien Lab from Jean Monnet University in Saint-Etienne, France, as a lecturer and researcher.
His principal fields of expertise are artificial intelligence, mathematical morphology, computer vision, 3D image reconstruction. Guillaume has contributed on several fields of applications: medicine (Diabetic Retinopathy and Cancer), life science (genomic prediction) and industry (quality control by AI and 3D imaging). He has been published in several journals and has obtained several patents (EU, USA, China, Japan) in these fields (https://cv.archives-ouvertes.fr/guillaume-noyel). He has led several scientific joint efforts between industry and public research centres.
Since 2023, Dr Noyel is a Senior Researcher at Limagrain in Artificial Intelligence and Computer Vision.
Publications
Publications
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Logarithmic Morphological Neural Nets robust to lighting variationsDGMM 2022, IAPR Second International Conference on Discrete Geometry and Mathematical Morphology, Oct 2022, Strasbourg, France. pp.462-474, ⟨10.1007/978-3-031-19897-7_36⟩ |
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Retinal vessel segmentation by probing adaptive to lighting variations2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), IEEE, Apr 2020, Iowa City, United States. pp.1246-1249, ⟨10.1109/ISBI45749.2020.9098332⟩ |
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Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortionsIEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), IEEE, Apr 2019, Venice, Italy. pp.561-564, ⟨10.1109/ISBI.2019.8759415⟩ |
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Logarithmic mathematical morphology: a new framework adaptive to illumination changes23rd Iberoamerican Congress on Pattern Recognition (CIARP 2018), Nov 2018, Madrid, Spain. pp.453-461, ⟨10.1007/978-3-030-13469-3_53⟩ |
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A Link Between the Multiplicative and Additive Functional Asplund’s Metrics14th International Symposium on Mathematical Morphology (ISMM 2019), Saarland University, Jul 2019, Saarbrücken, Germany. pp.41-53, ⟨10.1007/978-3-030-20867-7_4⟩ |
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Homogeneity of a region in the logarithmic image processing framework: application to region growing algorithmsPhysics and Mechanics of Random Structures: from Morphology to Material Properties, Jun 2018, Ile d'Oléron, France. pp.5-7 |
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A simple expression for the map of Asplund's distances with the multiplicative Logarithmic Image Processing (LIP) law12th European Congress for Stereology and Image Analysis 2017 (ECSIA 2017), University of Kaiserslautern; Fraunhofer-Institut für Techno- und Wirtschaftsmathematik (ITWM), Sep 2017, Kaiserslautern, Germany |
Enhancing Eye Fundus Images for Diabetic Retinopathy ScreeningAmerican Diabetes Association 77th Scientific Sessions - ADA2017, American Diabetes Association, Jun 2017, San Diego, CA, United States |
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Speeding up the Köhler's method of contrast thresholdingIEEE International Conference on Image Processing ICIP 2017, IEEE, Sep 2017, Beijing, China. ⟨10.1109/ICIP.2017.8296295⟩ |
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Double-sided probing by map of Asplund's distances using Logarithmic Image Processing in the framework of Mathematical Morphology13th International Symposium on Mathematical Morphology (ISMM 2017), May 2017, Fontainebleau, France. pp.408-420, ⟨10.1007/978-3-319-57240-6_33⟩ |
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Spatio-Colour Asplünd 's Metric and Logarithmic Image Processing for Colour Images (LIPC)21st Iberoamerican Congress on Pattern Recognition (CIARP 2016), International Association for Pattern Recognition (IAPR), Nov 2016, Lima, Peru. pp.36-43, ⟨10.1007/978-3-319-52277-7_5⟩ |
Contrast enhancement of eye fundus imagesIDF2015 - World Diabetes Congress, International Diabetes Federation, Nov 2015, Vancouver, Canada. ⟨10.13140/RG.2.1.3180.9367⟩ |
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Asplünd's metric defined in the Logarithmic Image Processing (LIP) framework for colour and multivariate imagesIEEE International Conference on Image Processing ICIP 2015, IEEE Signal Processing Society, Sep 2015, Québec City, Canada. pp.3921 - 3925, ⟨10.1109/ICIP.2015.7351540⟩ |
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Classification-Driven Stochastic Watershed: Application to Multispectral Segmentation4th European Conference on Colour in Graphics, Imaging, and Vision and 10th International Symposium on Multispectral Colour Science (CGIV 2008/MCS'08), Jun 2008, Terrassa - Barcelona, Spain. pp.471-476 |
Hyperspectral mathematical morphology applied to DCE-MRI series for angiogenesis imaging15th European Conference on Mathematics for Industry (ECMI'2008), University College London, Jul 2008, Londres, United Kingdom |
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Filtering, segmentation and region classification by hyperspectral mathematical morphology of DCE-MRI series for angiogenesis imaging5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2008), May 2008, Paris, France. pp.1517-1520, ⟨10.1109/ISBI.2008.4541297⟩ |
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Random Germs and Stochastic Watershed for Unsupervised Multispectral Image Segmentation11th International Conference Knowledge-Based Intelligent Information and Engineering Systems (KES 2007), Sep 2007, Vietri sul Mare, Salerno, Italy. pp.17-24, ⟨10.1007/978-3-540-74829-8_3⟩ |
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On distances, paths and connections for hyperspectral image segmentation8th International Symposium on Mathematical Morphology (ISMM 2007), Oct 2007, Rio de Janeiro, Brazil. pp.399-410 |
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Morphological segmentation of hyperspectral images - ICSXII12th International Congress for Stereology (ICS XII), Université Jean Monnet, Aug 2007, Saint-Etienne, France |
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Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortionsIEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), Apr 2019, Venice, Italy. , 2019 |
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Logarithmic mathematical morphology: a new framework adaptive to illumination changesCIARP2018 - 23rd Iberoamerican Congress on Pattern Recognition, Nov 2018, Madrid, Spain. , 2018 |
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Enhancing Eye Fundus Images for Diabetic Retinopathy ScreeningAmerican Diabetes Association 77th Scientific Sessions - ADA2017, Jun 2017, San Diego, CA, United States. , 608-P / 608, 2017 |
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Contrast enhancement of eye fundus imagesInternational Diabetes Federation. IDF2015 - World Diabetes Congress, Nov 2015, Vancouver, Canada. , IDF2015 - World Diabetes Congress 2015, 1110-P, 2015, ⟨10.13140/RG.2.1.3180.9367⟩ |
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Segmentations d'Images Hyperspectrales Par Morphologie MathématiqueEcole d'Hiver d'imagerie Numérique Couleur, Jan 2007, Poitiers, France |
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Regionalized Random Germs by a Classification for Probabilistic Watershed Application: Angiogenesis Imaging SegmentationAlistair D. Fitt, John Norbury, Hilary Ockendon, and Eddie Wilson. Progress in Industrial Mathematics at ECMI 2008, Springer, pp.211-216, 2010, Mathematics in Industry, 978-3-642-12109-8. ⟨10.1007/978-3-642-12110-4_29⟩ |
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Logarithmic Mathematical Morphology: theory and applications2023 |
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Filtrage, réduction de dimension, classification et segmentation morphologique hyperspectraleMathématiques [math]. École Nationale Supérieure des Mines de Paris, 2008. Français. ⟨NNT : 2008ENMP1558⟩ |
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Analyse morphologique et logarithmique de grandes banques d'imagesVision par ordinateur et reconnaissance de formes [cs.CV]. Université de Reims Champagne-Ardenne, 2021 |