Zobrazeno 1 - 10 of 34 pro vyhledávání: '"François Alin"'
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Akademický článek
Computer Vision and Deep Learning for Precision Viticulture
Autor: Lucas Mohimont, François Alin, Marine Rondeau, Nathalie Gaveau, Luiz Angelo Steffenel
Publikováno v: Agronomy, Vol 12, Iss 10, p 2463 (2022)
During the last decades, researchers have developed novel computing methods to help viticulturists solve their problems, primarily those linked to yield estimation of their crops. This article aims to summarize the existing research associated with c
Externí odkaz: https://doaj.org/article/e65fa0ae66be43b8b6f0369883d45689
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3
Convolutional neural networks and temporal CNNs for COVID-19 forecasting in France
Autor: Luiz Angelo Steffenel, Lucas Mohimont, François Alin, Michaël Krajecki, Amine Chemchem
Publikováno v: Applied Intelligence
Applied Intelligence, Springer Verlag (Germany), In press
HAL
International audience; THIS IS A PREPRINT for Applied Intelligence. The revised version is available here: https://link.springer.com/article/10.1007/s10489-021-02359-6This paper examines multiple CNN-based (Convolutional Neural Network) models for C
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25109f5fe1b2ba630e9d0cfb2cc01061
https://doi.org/10.1007/s10489-021-02359-6
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4
Lite CNN Models for Real-Time Post-Harvest Grape Disease Detection
Autor: Lucas Mohimont, François Alin, Nathalie Vaillant-Gaveau, Luiz Angelo Steffenel
Publikováno v: Workshop on Edge AI for Smart Agriculture (EAISA 2022)
Workshop on Edge AI for Smart Agriculture (EAISA 2022), Jun 2022, Biarritz, France
Workshops at 18th International Conference on Intelligent Environments
EAISA-Workshop on Edge AI for Smart Agriculture
EAISA-Workshop on Edge AI for Smart Agriculture, Jun 2022, Biarritz, France. pp.116-125, ⟨10.3233/AISE220029⟩
HAL
International audience; Post-harvest fruit grading is a necessary step to avoid disease related loss in quality. In this paper, a hierarchical method is proposed to (1) remove the background and (2) detect images that contains grape diseases(botrytis
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffec123406f0874b0f73c518eee75001
https://doi.org/10.3233/aise220029
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5
Comparison of Machine Learning and Deep Learning Methods for Grape Cluster Segmentation
Autor: François Alin, Marine Rondeau, Mathias Roesler, Nathalie Gaveau, Lucas Mohimont, Luiz Angelo Steffenel
Publikováno v: International Conference on Smart and Sustainable Agriculture (SSA'2021)
International Conference on Smart and Sustainable Agriculture (SSA'2021), Jun 2021, virtual, France. pp.84-102, ⟨10.1007/978-3-030-88259-4_7⟩
Communications in Computer and Information Science
Communications in Computer and Information Science-Smart and Sustainable Agriculture
Smart and Sustainable Agriculture ISBN: 9783030882587
International audience
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f07583d581acd1aba23456274063450
https://hal.univ-reims.fr/hal-03426932
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6
Deploying Deep Neural Networks on Edge Devices for Grape Segmentation
Autor: Nathalie Gaveau, François Alin, Luiz Angelo Steffenel, Mathias Roesler, Lucas Mohimont
Publikováno v: International Conference on Smart and Sustainable Agriculture (SSA'2021)
International Conference on Smart and Sustainable Agriculture (SSA'2021), Jun 2021, virtual, France. pp.30-43, ⟨10.1007/978-3-030-88259-4_3⟩
International Conference on Smart and Sustainable Agriculture
Communications in Computer and Information Science
Communications in Computer and Information Science-Smart and Sustainable Agriculture
Smart and Sustainable Agriculture ISBN: 9783030882587
Deep learning (DL) is a hot trend for object detection and segmentation, thanks to the use of Deep Neural Networks (DNNs). Image recognition is a powerful tool for precision viticulture, having a strong potential in cases such as yield estimation and
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ea42d938a7cd25864ce94a7c1562a3d
https://hal.univ-reims.fr/hal-03426929
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7
AI-Driven Yield Estimation Using an Autonomous Robot for Data Acquisition
Autor: Lucas Mohimont, Mathias Roesler, Luiz Angelo Steffenel, Nathalie Gaveau, Marine Rondeau, François Alin, Clément Pierlot, Rachel Ouvinha de Oliveira, Marcello Coppola, Philipe Doré
Publikováno v: Artificial Intelligence for Digitising Industry Applications
Artificial Intelligence for Digitising Industry Applications, River Publishers, pp.289-300, 2021, 9788770226646
HAL
International audience; The quality of the harvest depends significantly on the quality of the grapes. Therefore, winemakers need to make the right decisions to obtain highquality grapes. One of the first problems is estimating the yield of the crops
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::13a9b9c18bf74645f11614adb297dd00
https://hal.univ-reims.fr/hal-03355290
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8
Traitement d’Images et Apprentissage Automatique pour la Viticulture de Précision
Autor: Marine Rondeau, Lucas Mohimont, François Alin, Mathias Roesler, Nathalie Gaveau, Amine Chemchem, Luiz Angelo Steffenel
Publikováno v: Revue Ouverte d'Intelligence Artificielle
Revue Ouverte d'Intelligence Artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
Revue ouverte d'intelligence artificielle
Revue ouverte d'intelligence artificielle, 2021, 2 (1), pp.33-63. ⟨10.5802/roia.9⟩
National audience
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c42ecca8a27ffdba79e49b184a135d98
https://hal.univ-reims.fr/hal-03437912
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9
Combining SMOTE Sampling and Machine Learning for Forecasting Wheat Yields in France
Autor: François Alin, Michaël Krajecki, Amine Chemchem
Publikováno v: AIKE
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), 2019, Cagliari, Italy. ⟨10.1109/AIKE.2019.00010⟩
International audience; This paper describes a method of predicting wheat yields based on machine learning, which accurately determines the value of wheat yield losses in France. Obtaining reliable value from yield losses is difficult because we are
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3f252d115813782b1ed42e5b0ad1bc0
https://doi.org/10.1109/aike.2019.00010
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10
Towards a Hierarchical Deep Learning Approach for Intrusion Detection
Autor: Olivier Flauzac, François Alin, Amine Chemchem, Michaël Krajecki, Florent Nolot
Publikováno v: Machine Learning for Networking Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3–5, 2019, Revised Selected Papers
International Conference on Machine Learning for Networking (MLN)
International Conference on Machine Learning for Networking (MLN), 2019, Paris, France. ⟨10.1007/978-3-030-45778-5_2⟩
Machine Learning for Networking ISBN: 9783030457778
MLN
International audience; Nowadays, it is almost impossible to imagine our daily life without Internet. This strong dependence requires an effective and rigorous consideration of all the risks related to computer attacks. However traditional methods of
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fe2beb779d800206383f22ce8a2c349
https://hal.archives-ouvertes.fr/hal-02560294/document
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