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FC
Frédéric Cointault
19
Documents
Identifiants chercheurs
- frederic-cointault
- 0000-0001-8541-8382
- IdRef : 060721561
Présentation
Publications
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Feasibility of selecting optimal textural features to detect foliar symptoms of ‘flavescence doree’ grapevine diseaseIEEE 3rd International Conference on Signal and Image Processing (ICSIP), Jul 2018, Shenzhen, China
Communication dans un congrès
hal-02733552v1
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High resolution imagery for phenotypic root traits detectionCIRG-AgEng 2016, International Conférence on Agricultural Engineering, Automation, Environment and Food Safety, Jun 2016, Aarhus, Denmark
Communication dans un congrès
hal-01607093v1
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Automatic detection of nodules in legumes by imagery in a phenotyping context16. International Conference on Computer Analysis of Images and Patterns (CAIP 2015), Sep 2015, Valletta, Malta. ⟨10.1007/978-3-319-23117-4_12⟩
Communication dans un congrès
hal-02741403v1
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Automatic detection of phenotypic traits in legume roots3. International Workshop on Image Analysis Methods for the Plant Sciences, 2014
Communication dans un congrès
hal-02740502v1
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Noise Robustness of a Texture Classification Protocol for Natural Leaf Roughness Characterisation9th International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2012), Jun 2012, Crète, Greece. pp. 64-68, ⟨10.2316/P.2012.778-051⟩
Communication dans un congrès
hal-00822439v1
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Vineyard leaf roughness characterization by computer vision and cloud computing technicsInternational Conference on Agricultural Engineering-AgEng 2010, Sep 2010, Clermont-Ferrand, France. pp.309
Communication dans un congrès
hal-00842218v1
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A new tool for assessment of biostimulants effects on grapevinePoster de conférence hal-02785861v1 |
Protocol for the Definition of a Multi-Spectral Sensor for Specific Foliar Disease Detection: Case of “Flavescence Dorée”Phytoplasmas : Methods and Protocols, pp.213-238, 2019, 978-1-4939-8837-2. ⟨10.1007/978-1-4939-8837-2_17⟩
Chapitre d'ouvrage
hal-02067306v1
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Protocol for the definition of a multi-spectral sensor for specific foliar disease detection: case of “Flavescence Dorée”Phytoplasma – Methods and Protocols, 1875, Springer, 2019
Chapitre d'ouvrage
hal-02787283v1
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3D imaging systems for agricultural applicationsDeveloping and applying optoelectronics in machine vision, IGI Global, 344 p., 2017, Advances in Computational Intelligence and Robotics (ACIR), 2327-0411 ISBN13: 9781522506324|ISBN10: 1522506322. ⟨10.4018/978-1-5225-0632-4.ch008⟩
Chapitre d'ouvrage
hal-01605252v1
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3D imaging systems for agricultural applications: characterization of crop and root phenotypingDeveloping and applying optoelectronics in machine vision. Sergiyenko, O. and Rodriguez-Quiñonez, J.C., IGI Global, pp.236-272, 2016
Chapitre d'ouvrage
hal-02604540v1
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