1 code implementation • 10 Jan 2024 • Joaquim Estopinan, Pierre Bonnet, Maximilien Servajean, François Munoz, Alexis Joly
Cross-validation yields average accuracies of 0. 61 for status classification and 0. 78 for binary classification.
no code implementations • 9 Jan 2024 • Joaquim Estopinan, Maximilien Servajean, Pierre Bonnet, Alexis Joly, François Munoz
In Sumatra, we found good correspondence of protected areas with our indicators, but supplementing current IUCN assessments with status predictions results in alarming levels of species threat across the island.
no code implementations • 7 Aug 2023 • Christophe Botella, Benjamin Deneu, Diego Marcos, Maximilien Servajean, Joaquim Estopinan, Théo Larcher, César Leblanc, Pierre Bonnet, Alexis Joly
We designed a European scale dataset covering around ten thousand plant species to calibrate and evaluate SDM predictions of species composition in space and time at high spatial resolution (~ten meters), and their spatial transferability.
no code implementations • 31 Mar 2023 • Camille Garcin, Maximilien Servajean, Alexis Joly, Joseph Salmon
Average-K classification is an alternative to top-K classification in which the number of labels returned varies with the ambiguity of the input image but must average to K over all the samples.
no code implementations • 30 Sep 2022 • Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon
We adapt the AUM to identify ambiguous tasks in crowdsourced learning scenarios, introducing the Weighted Areas Under the Margin (WAUM).
no code implementations • 17 Aug 2022 • Quentin Leroy, Olivier Buisson, Alexis Joly
We hypothesize that incorporating unlabelled images of novel classes in the training set in a semi-supervised fashion would be beneficial for the efficient retrieval of novel-class images compared to a vanilla supervised representation.
1 code implementation • 4 Feb 2022 • Camille Garcin, Maximilien Servajean, Alexis Joly, Joseph Salmon
In modern classification tasks, the number of labels is getting larger and larger, as is the size of the datasets encountered in practice.
no code implementations • 16 Dec 2021 • Titouan Lorieul, Alexis Joly, Dennis Shasha
This paper formally characterizes the ambiguity profile when average-$K$ classification can achieve a lower error rate than a fixed top-$K$ classification.
no code implementations • 4 Aug 2021 • Daniel Rosendo, Alexandru Costan, Gabriel Antoniu, Matthieu Simonin, Jean-Christophe Lombardo, Alexis Joly, Patrick Valduriez
We propose a methodology to support the optimization of real-life applications on the Edge-to-Cloud Continuum.
no code implementations • 5 Feb 2021 • Rafael S. Pereira, Alexis Joly, Patrick Valduriez, Fabio Porto
However, this traditional approach is not useful for identifying classes unseen on the training set, known as the open set problem.
1 code implementation • 8 Apr 2020 • Elijah Cole, Benjamin Deneu, Titouan Lorieul, Maximilien Servajean, Christophe Botella, Dan Morris, Nebojsa Jojic, Pierre Bonnet, Alexis Joly
Understanding the geographic distribution of species is a key concern in conservation.
no code implementations • 27 Nov 2019 • Julien Herrmann, Olivier Beaumont, Lionel Eyraud-Dubois, Julien Hermann, Alexis Joly, Alena Shilova
This paper introduces a new activation checkpointing method which allows to significantly decrease memory usage when training Deep Neural Networks with the back-propagation algorithm.
no code implementations • 19 Sep 2019 • Benjamin Deneu, Maximilien Servajean, Christophe Botella, Alexis Joly
This paper presents an evaluation of several approaches of plants species distribution modeling based on spatial, environmental and co-occurrences data using machine learning methods.