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Aller à 2023 | 2021 | 2020 | 2017

Nombre de documents : 8.

2023

Coupling plant growth models and pest and disease models: An interaction structure proposal, MIMIC. Triki Houssem, Ribeyre Fabienne, Pinard Fabrice, Jaeger Marc. 2023. Plant Phenomics, 5:0077, 15 p.
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GrapeInSilico: a modelling framework for building grapevine FSPMs. Delivorias Stathis, Albasha Rami, Calonnec Agnès, Vivin Philippe, Pradal Christophe, Pallas Benoît, Fournier Christian. 2023. In : Book of abstracts the 10th International Conference on Functional-Structural Plant Models (FSPM2023). Tsu-Wei Chen (ed.), Andreas Fricke (ed.), Katrin Kahlen (ed.), Susann Müller (ed.), Hartmut Stützel (ed.). Hannover : Institute of Horticultural Production Systems, 144-145. International Conference on Functional-Structural Plant Models (FSPM2023). 10, Berlin, Allemagne, 27 Mars 2023/31 Mars 2023.
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SNEToolkit: Spatial named entities disambiguation toolkit. Kafando Rodrique, Decoupes Rémy, Roche Mathieu, Teisseire Maguelonne. 2023. SoftwareX, 23:101480, 11 p.
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2021

Fijiyama: A registration tool for 3D multimodal time-lapse imaging. Fernandez Romain, Moisy Cédric. 2021. Bioinformatics, 37 (10) : 1482-1484.
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PADI-web 3.0: A new framework for extracting and disseminating fine-grained information from the news for animal disease surveillance. Valentin Sarah, Arsevska Elena, Rabatel Julien, Falala Sylvain, Mercier Alizé, Lancelot Renaud, Roche Mathieu. 2021. One Health, 13:100357, 10 p.
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2020

SHiNeMaS: a web tool dedicated to seed lots history, phenotyping and cultural practices. De Oliveira Yannick, Burlot Laura, Dawson Julie C., Goldringer Isabelle, Madi Darkawi, Rivière Pierre, Steinbach Delphine, Van Frank Gaëlle, Thomas Mathieu. 2020. Plant Methods, 16:98, 9 p.
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lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Roussel Jean-Romain, Auty David, Coops Nicholas C., Tompalski Piotr, Goodbody Tristan R.H., Sánchez Meador Andrew, Bourdon Jean-François, De Boissieu Florian, Achim Alexis. 2020. Remote Sensing of Environment, 251:112061, 15 p.
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2017

SSDM : An R package to predict distribution of species richness and composition based on stacked species distribution models. Schmitt Sylvain, Pouteau Robin, Justeau-Allaire Dimitri, De Boissieu Florian, Birnbaum Philippe. 2017. Methods in Ecology and Evolution, 8 (12) : 1795-1803.
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