| A review of data cleaning approaches in a hydrographic framework with a focus on bathymetric multibeam echosounder datasets J Le Deunf, N Debese, T Schmitt, R Billot Geosciences 10 (7), 254, 2020 | 42 | 2020 |
| Results from the first phase of the seafloor backscatter processing software inter-comparison project M Malik, ACG Schimel, G Masetti, M Roche, J Le Deunf, MFJ Dolan, ... Geosciences 9 (12), 516, 2019 | 8 | 2019 |
| Outlier detection for Multibeam echo sounder (MBES) data: From past to present D Nathalie, S Thierry, G François, J Etienne, V Lucas, B Romain OCEANS 2019-Marseille, 1-10, 2019 | 7 | 2019 |
| Automating the Management of 300 Years of Ocean Mapping Effort in Order to Improve the Production of Nautical Cartography and Bathymetric Products: Shom’s Téthys Workflow J Le Deunf, T Schmitt, Y Keramoal, R Jarno, M Fally Geomatics 3 (1), 239-249, 2023 | 3 | 2023 |
| Automatic data quality assessment of hydrographic surveys taking into account experts’ preferences J Le Deunf, A Khannoussi, L Lecornu, P Meyer, J Puentes OCEANS 2021: San Diego–Porto, 1-10, 2021 | 3 | 2021 |
| Multibeam outlier detection by clustering and topological persistence approach, ToMATo algorithm M Michel, J Le Deunf, N Debese, L Bazinet, L Dejoie OCEANS 2021: San Diego–Porto, 1-8, 2021 | 3 | 2021 |
| A pragmatical algorithm to compute the convex envelope of bathymetric surveys at variable resolutions J Le Deunf, T Schmitt, Y Keramoal Abstracts of the ICA 3, 1-2, 2021 | 1 | 2021 |
| Téthys: automating a data workflow compiling over 300 years of bathymetric information J Le Deunf, R Jarno, Y Keramoal, T Schmitt, M Fally, L Biscara, J Dubuis OCEANS 2021: San Diego–Porto, 1-6, 2021 | 1 | 2021 |
| A DEEP SEGMENTATION APPROACH FOR MULTIBEAM ECHO SOUNDER BACKSCATTER DATA BASED ON SEAFLOOR TYPE H Moreau, S Homrani, I Mopin, J Le Deunf, J Bignon, G Le Chenadec ICUA2024, 2024 | | 2024 |
| Data quality assessment through a preference model J Le Deunf, A Khannoussi, L Lecornu, P Meyer, J Puentes ACM Journal of Data and Information Quality 16 (1), 1-21, 2024 | | 2024 |
| Apprentissage automatique de données massives bathymétriques pour l'optimisation de systèmes de levé hydrographique J Le Deunf Ecole nationale supérieure Mines-Télécom Atlantique, 2022 | | 2022 |
| Machine learning on massive bathymetric data for the optimization of hydrographic survey systems J Le Deunf Ecole nationale supérieure Mines-Télécom Atlantique, 2022 | | 2022 |
| ALGORITHME PRAGMATIQUE POUR CALCULER L’ENVELOPPE DES LEVÉS BATHYMÉTRIQUES À DENSITÉ VARIABLE J Le Deunf, T Schmitt, Y Keramoal Cartes et Géomatique, 2022 | | 2022 |
| Seabed prediction from airborne topo-bathymetric lidar point cloud using machine learning approaches J Le Deunf, R Mishra, Y Pastol, R Billot, S Oudot OCEANS 2021: San Diego–Porto, 1-9, 2021 | | 2021 |
| Integrating user preferences in the automatic quality assessment of hydrographic surveys A Khannoussi, J Le Deunf, P Meyer, L Lecornu, J Puentes The 92nd Meeting of EURO Working Group on Multicriteria Decision Aiding, 2021 | | 2021 |
| Utilisation d'infrastructures géodésiques mondiales pour la réalisation nationale R Legouge, A Gaël, A Missault, J Le Deunf, S Branchu Revue XYZ 158, 2019 | | 2019 |
| Exploration du lac de Guerlédan: présentation des projets étudiants en hydrographie et acoustique sous-marine I Mopin, R Schwab, C Vrignaud, L Berger, J Le Deunf Congrès Français d’Acoustique, CFA 2018, 2018 | | 2018 |
| Master Thesis Report J Le Deunf | | |
Romain BILLOTFull Professor, IMT Atlantique在 imt-atlantique.fr 的电子邮件经过验证
