Gautron, Romain Maillard, Odalric-Ambrym Preux, Philippe Corbeels, Marc Sabbadin, Régis
Reinforcement learning (RL), including multi-armed bandits, is a branch of machine learning that deals with the problem of sequential decision-making in uncertain and unknown environments through learning by practice. While best known for being the core of the artificial intelligence (AI) world's best Go game player, RL has a vast range of potentia...
Valentin, Sarah Mercier, Alizé Lancelot, Renaud Roche, Mathieu Arsevska, Elena
Event‐based surveillance (EBS) systems monitor a broad range of information sources to detect early signals of disease emergence, including new and unknown diseases. In December 2019, a newly identified coronavirus emerged in Wuhan (China), causing a global coronavirus disease (COVID‐19) pandemic. A retrospective study was conducted to evaluate the...
Ezanno, Pauline Picault, Sébastien Beaunée, Gaël Bailly, Xavier Munoz, Facundo Duboz, Raphaël Monod, Hervé Guégan, Jean-François
Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to mor...
August, Tom A. Pescott, Oliver L. Joly, Alexis Bonnet, Pierre
The increasing availability of digital images, coupled with sophisticated artificial intelligence (AI) techniques for image classification, presents an exciting opportunity for biodiversity researchers to create new datasets of species observations. We investigated whether an AI plant species classifier could extract previously unexploited biodiver...
Bonnet, Pierre Goeau, Hervé Hopkins, Frantz Vela, Errol Sahl, Amandine Affouard, Antoine Lombardo, Jean-Christophe Champ, Julien Gresse, Hugo Joly, Alexis
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La diversité des habitats du Parc national des Cévennes héberge une flore riche, composée de plus de 2400 espèces (angiospermes, gymnospermes et fougères). Une bonne connaissance de cette flore est essentielle pour le développement de stratégies de gestion adaptées. Les ressources humaines étant cependant limitées, l'appui des résidents et visiteur...
Bonnet, Pierre Joly, Alexis Faton, Jeaqn-Michel Brown, Susan Kimiti, David Deneu, Benjamin Servajean, Maximilien Affouard, Antoine Lombardo, Jean-Christophe Mary, Laura
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1. Successful monitoring and management of plant resources worldwide needs the involvement of civil society to support natural reserve managers. Because it is difficult to correctly and quickly identify plant species for non‐specialists, the development of recent techniques based on automatic visual identification should facilitate and increase pub...
Bonnet, Pierre Champ, Julien Goeau, Hervé Stöter, Fabian-Robert Deneu, Benjamin Servajean, Maximilien Affouard, Antoine Lombardo, Jean-Christophe Levchenko, Oleksandra Gresse, Hugo
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[email protected] is a scientific and citizen platform based on artificial intelligence techniques to help participants more easily identify plants with their smartphones. The identification of plant species is indeed an important step for many scientific, educational and land management activities (for natural or cultivated spaces). This step, which is int...
Alburez-Gutierrez, Diego Chandrasekharan, Eshwar Chunara, Rumi Gil-Clavel, Sofia Hannak, Aniko Interdonato, Roberto Joseph, Kenneth Kalimeri, Kyriaki Malik, Momin M. Mayer, Katja
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The workshop program of the Association for the Advancement of Artificial Intelligence's 13th International Conference on Web and Social Media was held at the Bavarian School of Public Policy in Munich, Germany on June 11, 2019. There were five full-day workshops, one half-day workshop, and the annual evening Science Slam in the program. The procee...
Varala, Kranthi Marshall-Colón, Amy Cirrone, Jacopo Brooks, Matthew D. Pasquino, Angelo V. Leran, Sophie Mittal, Shipra Rock, Tara M. Edwards, Molly B. Kim, Grace J.
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This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our “just-in-time” analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer ...
Müller, Jean Pierre