Résultats pour : "apprentissage machine"

Combining UAV and sentinel-2 imagery for estimating millet FCover in an heterogeneous agricultural landscape of Senegal. Diack Ibrahima, Diene Serigne Mansour, Leroux Louise, Diouf Abdoul Aziz, Heuclin Benjamin, Roupsard Olivier, Letourmy Philippe, Audebert Alain, Sarr Idrissa, Diallo Moussa. 2024. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17 : 7305-7322.

Discriminating Robusta coffee (Coffea canephora) cropping systems using leaf-level hyperspectral data. Kebede Getachew, Mudereri Bester Tawona, Abdel-Rahman Elfatih M., Mutanga Onisimo, Landmann Tobias, Odindi John, Motisi Natacha, Pinard Fabrice, Tonnang Henri E.Z.. 2024. Journal of Applied Remote Sensing, 18 (4), 17 p.

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotying of grapevine trunk internal structure. Fernandez Romain, Le Cunff Loïc, Merigeaud Samuel, Verdeil Jean-Luc, Perry Julie, Larignon Philippe, Spilmont Anne-Sophie, Chatelet Philippe, Cardoso Maida, Goze-Bac Christophe, Moisy Cédric. 2024. Scientific Reports, 14:5033, 14 p.

Generating high-resolution land use and land cover maps for the greater Mariño watershed in 2019 with machine learning. Vallet Ameline, Dupuy Stéphane, Verlynde Matthieu, Gaetano Raffaele. 2024. Scientific Data, 11:915, 14 p.

Global patterns of tree wood density. Yang Hui, Wang Siyuan, Son Rackhun, lee Hoontaek, Benson Vitus, Zhang Weijie, Zhang Yahai, Zhang Yuzhen, Kattge Jens, Boenisch Gerhard, Schepaschenko Dmitry, Karaszewski Zbigniew, Stereńczak Krzysztof, Moreno-Martínez Álvaro, Nabais Cristina, Birnbaum Philippe, Vieilledent Ghislain, Weber Ulrich, Carvalhais Nuno. 2024. Global Change Biology, 30 (3):e17224, 13 p.

Improving pearl millet yield estimation from UAV imagery in the semiarid agroforestry system of Senegal through textural indices and reflectance normalization. Diene Serigne Mansour, Diack Ibrahima, Audebert Alain, Roupsard Olivier, Leroux Louise, Diouf Abdoul Aziz, Mbaye Modou, Fernandez Romain, Diallo Moussa, Sarr Idrissa. 2024. IEEE Access, 18 p.

Linking genetic markers and crop model parameters using neural networks to enhance genomic prediction of integrative traits. Larue Florian, Rouan Lauriane, Pot David, Rami Jean-François, Luquet Delphine, Beurier Grégory. 2024. Frontiers in Plant Science, 15:1393965, 13 p.

Multivariate regional deep learning prediction of soil properties from near-infrared, mid-infrared and their combined spectra. Nyawasha Rumbidzai, Wadoux Alexandre M. J. C., Todoroff Pierre, Chikowo Régis, Falconnier Gatien, Lagorsse Maeva, Corbeels Marc, Cardinael Rémi. 2024. Geoderma Regional, 37:e00805, 11 p.

Advances in plant imaging across scales. Soltis Pamela S., Teixeira‐Costa Luiza, Bonnet Pierre, Nelson Gil. 2023. Applications in Plant Sciences, 11 (5), n.spéc. Advances in Plant Imaging across Scales:11550, 4 p.

Animal disease surveillance: How to represent textual data for classifying epidemiological information. Valentin Sarah, Decoupes Rémy, Lancelot Renaud, Roche Mathieu. 2023. Preventive Veterinary Medicine, 216:105932, 9 p.

Characterization of rice yield based on biomass and SPAD-based leaf nitrogen for large genotype plots. Duque Andres F., Patino Diego, Colorado Julian D., Petro Eliel, Rebolledo Maria Camila, Mondragon Ivan F., Espinosa Natalia, Amezquita Nelson, Puentes Oscar D., Mendez Diego, Jaramillo-Botero Andres. 2023. Sensors, 23 (13), n.spéc. Sensors and Artificial Intelligence in Smart Agriculture:5917, 21 p.

Deep semi-supervised clustering for multi-variate time-series. Ienco Dino, Interdonato Roberto. 2023. Neurocomputing, 516 : 36-47.

Envisaging a global infrastructure to exploit the potential of digitised collections. Groom Quentin, Dillen Mahtias, Addink Wouter, Ariño Arturo H., Bölling Christian, Bonnet Pierre, Cecchi Lorenzo, Ellwood Elizabeth R., Figueira Rui, Gagnier Pierre-Yves, Grace Olwen, Güntsch Anton, Hardy Helen, Huybrechts Pieter, Hyam Roger, Joly Alexis, Kommineni Vamsi Krishna, Larridon Isabel, Livermore Laurence, Lopes Ricardo Jorge, Meeus Sofie, Miller Jeremy, Milleville Kenzo, Panda Renato, Pignal Marc, Poelen Jorrit, Ristevski Blagoj, Robertson Tim, Rufino Ana C., Santos Joaquim, Schermer Maarten, Scott Ben, Seltmann Katja Chantre, Teixeira Heliana, Trekels Maarten, Gaikwad Jitendra. 2023. Biodiversity Data Journal, 11:e109439, 29 p.

Temporal-domain adaptation for satellite image time-series land-cover mapping with adversarial learning and spatially aware self-training. Capliez Emmanuel, Ienco Dino, Gaetano Raffaele, Baghdadi Nicolas, Salah Adrien Hadj. 2023. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16 : 3645-3675.

Understanding climate change effects on the potential distribution of an important pollinator species, Ceratina moerenhouti (Apidae: Ceratinini), in the Eastern Afromontane biodiversity hotspot, Kenya. Mukundamago Mukundi, Dube Timothy, Mudereri Bester Tawona, Babin Régis, Lattorff H. Michael G., Tonnang Henri E.Z.. 2023. Physics and Chemistry of the Earth, 130:103387, 14 p.

VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Madec Simon, Irfan Kamran, Velumani Kaaviya, Baret Frédéric, David Etienne, Daubige Gaetan, Bernigaud Samatan Lucas, Serouart Mario, Smith Daniel, James Chrisbin, Camacho Fernando, Guo Wei, De Solan Benoit, Chapman Scott, Weiss Marie. 2023. Scientific Data, 10:302, 12 p.

A constrastive semi-supervised deep learning framework for land cover classification of satellite time series with limited labels. Ienco Dino, Gaetano Raffaele, Interdonato Roberto. 2023. Neurocomputing, 567:127031, 11 p.

Food security prediction from heterogeneous data combining machine and deep learning methods. Deleglise Hugo, Interdonato Roberto, Bégué Agnès, Maître d'Hôtel Elodie, Teisseire Maguelonne, Roche Mathieu. 2022. Expert Systems with Applications, 190:116189, 11 p.

Impact of recursive feature elimination with cross-validation in modeling the spatial distribution of three mosquito species in Morocco. Douider Meriem, Amrani Ibrahim, Balenghien Thomas, Bennouna Amal, Abik Mounia. 2022. Revue d'Intelligence Artificielle, 36 (6) : 855-862.

Modelling the functional dependency between root and shoot compartments to predict the impact of the environment on the architecture of the whole plant: Methodology for model fitting on simulated data using Deep Learning techniques. Masson Abel Louis, Caraglio Yves, Nicolini Eric-André, Borianne Philippe, Barczi Jean-François. 2022. In Silico Plants, 4 (1):diab036, 20 p.

Reinforcement learning for crop management support: Review, prospects and challenges. Gautron Romain, Maillard Odalric-Ambrym, Preux Philippe, Corbeels Marc, Sabbadin Régis. 2022. Computers and Electronics in Agriculture, 200:107182, 14 p.

A divide-and-conquer approach for genomic prediction in rubber tree using machine learning. Hild Aono Alexandre, Francisco Felipe Roberto, Moura Souza Livia, De Souza Gonçalves Paulo, Scaloppi Junior Erivaldo José, Le Guen Vincent, Fritsche-Neto Roberto, Gorjanc Gregor, Gonçalves Quiles Marcos, Pereira de Souza Anete. 2022. Scientific Reports, 12:18023, 14 p.

Assessing the sensitivity of global maize price to regional productions using statistical and machine learning methods. Zelingher Rotem, Makowski David, Brunelle Thierry. 2021. Frontiers in Sustainable Food Systems, 5:655206, 11 p.

Hierarchical classification of very small objects: Application to the detection of arthropod species. Tresson Paul, Carval Dominique, Tixier Philippe, Puech William. 2021. IEEE Access, 9 : 63925-63932.

High probability of yield gain through conservation agriculture in dry regions for major staple crops. Su Yang, Gabrielle Benoît, Beillouin Damien, Makowski David. 2021. Scientific Reports, 11:3344, 8 p.

Innovative measurements to drive sustainable agriculture: The agroecology case. Dumet Didier, Cousin Philippe, Husson Olivier, Rollet Martin, Levavasseur Vincent. 2021. Journal of Advanced Agricultural Technologies, 8 (2) : 60-66.

Potassium nutrition in oil palm: The potential of metabolomics as a tool for precision agriculture. Cui Jing, Chao de la Barca Juan Manuel, Lamade Emmanuelle, Tcherkez Guillaume. 2021. Plants, People, Planet, 3 (4) : 350-354.

AI naturalists might hold the key to unlocking biodiversity data in social media imagery. August Tom A., Pescott Oliver L., Joly Alexis, Bonnet Pierre. 2020. Patterns, 1 (7):100116, 11 p.

Discovering weather periods and crop properties favorable for coffee rust incidence from feature selection approaches. Lasso Emmamnuel, Corrales David Camilo, Avelino Jacques, de Melo Virginio Filho Elias, Corrales Juan Carlos. 2020. Computers and Electronics in Agriculture, 176:105640, 11 p.

Landscape fragmentation in coffee agroecological subzones in central Kenya: A multiscale remote sensing approach. Mosomtai Gladys, Odindi John, Abdel-Rahman Elfatih M., Babin Régis, Pinard Fabrice, Mutanga Onisimo, Tonnang Henri E.Z., David Guillaume, Landmann Tobias. 2020. Journal of Applied Remote Sensing, 14 (4):044513, 20 p.

Landscape-scale spatial modelling of deforestation, land degradation, and regeneration using machine learning tools. Grinand Clovis, Vieilledent Ghislain, Razafimbelo Tantely Maminiana, Rakotoarijaona Jean-Roger, Nourtier Marie, Bernoux Martial. 2020. Land Degradation and Development, 31 (13) : 1699-1712.

Machine learning using digitized herbarium specimens to advance phenological research. Pearson Katelin D., Nelson Gil, Aronson Myla F.J., Bonnet Pierre, Brenskelle Laura, Davis Charles C., Denny Ellen G., Ellwood Elizabeth R., Goeau Hervé, Heberling J. Mason, Joly Alexis, Lorieul Titouan, Mazer Susan J., Meineke Emily K., Stucky Brian J., Sweeney Patrick W., White Alexander E., Soltis Pamela S.. 2020. BioScience, 70 (7) : 610-620.

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning. Cuéllar Ana Carolina, Kjaer Lene Jung, Baum Andreas, Stockmarr Anders, Skovgard Henrik, Nielsen Soren Achim, Andersson Mats Gunnar, Lindstrom Anders, Chirico Jan, Lühken Renke, Steinke Sonja, Kiel Ellen, Gethmann Jörn M., Conraths Franz J., Larska Magdalena, Smreczak Marcin, Orlowska Anna, Hammes Inger, Sviland Stale, Hopp Petter, Brugger Katharina, Rubel Franz, Balenghien Thomas, Garros Claire, Rakotoarivony Ignace, Allene Xavier, Lhoir Jonathan, Chavernac David, Delecolle Delphine, Mathieu Bruno, Delecolle Delphine, Setier Rio Marie-Laure, Scheid Bethsabée, Miranda Chueca Miguel Ángel, Barcelo Carlos, Lucientes Javier, Estrada Rosa, Mathis Alexander, Venail Roger, Tack Wesley, Bodker René. 2020. Parasites and Vectors, 13:194, 18 p.

Serendipitous learning fostered by brain state assessment and collective wisdom. Cerri Stefano A., Lemoisson Philippe. 2020. In : Brain function assessment in learning: Second International Conference, BFAL 2020, Heraklion, Crete, Greece, October 9–11, 2020, Proceedings. Frasson Claude (ed.), Bamidis Panagiotis (ed.), Vlamos Panagotis (ed.). IIS. Cham : Springer, 125-136. (Lecture Notes in Artificial Intelligence, 12462) ISBN 978-3-030-60734-0 International Conference on Brain Function Assessment in Learning (BFAL 2020). 2, Crète, Grèce, 9 Octobre 2020/11 Octobre 2020.

Accelerating the automated detection, counting and measurements of reproductive organs in herbarium collections in the era of deep learning. Mora-Fallas Adán, Goeau Hervé, Mazer Susan J., Love Natalie, Mata-Montero Erick, Bonnet Pierre, Joly Alexis. 2019. Biodiversity Information Science and Standards, 3:e37341, 3 p. Biodiversity Next: Building a global infrastructure for biodiversity data, Leiden, Pays-Bas, 22 Octobre 2019/25 Octobre 2019.

Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: Potential and limitations of physical modeling and machine learning. Feret Jean Baptiste, Le Maire Guerric, Jay Sylvain, Berveiller Daniel, Bendoula Ryad, Hmimina Gabriel, Cheraiet A., Oliveira J.C., Ponzoni Flávio Jorge, Solanki T., De Boissieu Florian, Chave Jérôme, Nouvellon Yann, Porcar-Castell A., Proisy Christophe, Soudani Kamel, Gastellu-Etchegorry J.P., Lefèvre-Fonollosa Marie-José. 2019. Remote Sensing of Environment, 231:110959, 14 p.

Factors affecting the dynamics of frosty pod rot in the main cocoa areas of Santander State, Colombia. Jaimes Yeirme, Ribeyre Fabienne, Gonzalez Carolina, Rojas Jairo, Furtado Edson L., Cilas Christian. 2019. Plant Disease, 103 (7) : 1665-1673.

GECKO is a genetic algorithm to classify and explore high throughput sequencing data. Thomas Aubin, Barriere sylvain, Broseus Lucile, Brooke Julie, Lorenzi Claudio, Villemin Jean-Philippe, Beurier Grégory, Sabatier Robert, Reynes Christelle, Mancheron Alban, Ritchie William. 2019. Communications Biology, 2:222, 8 p.

Mapping land cover on Reunion Island in 2017 using satellite imagery and geospatial ground data. Dupuy Stéphane, Gaetano Raffaele, Le Mézo Lionel. 2019. Data in Brief, 28:104934, 12 p.

Observation des caractères racinaires au champ : apport de l'apprentissage automatique. Postic Francois. 2019. Le Sélectionneur Français (70) : 47-51. Journée Scientifique ASF, Versailles, France, 7 Février 2019.

Going deeper in the automated identification of Herbarium specimens. Carranza-Rojas Jose Mario, Goeau Hervé, Bonnet Pierre, Mata-Montero Erick, Joly Alexis. 2017. BMC Evolutionary Biology, 17:e181, 14 p.

A robot-assisted imaging pipeline for tracking the growths of maize ear and silks in a high-throughput phenotyping platform. Brichet Nicolas, Fournier Christian, Turc Olivier, Strauss Olivier, Artzet Simon, Pradal Christophe, Welcker Claude, Tardieu François, Cabrera-Bosquet Llorenç. 2017. Plant Methods, 13:96, 12 p.