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pro vyhledávání: '"A. Lefebvre"'
Autor:
R. Halawi Ghosn, É. Poisson-Caillault, G. Charria, A. Bonnat, M. Repecaud, J.-V. Facq, L. Quéméner, V. Duquesne, C. Blondel, A. Lefebvre
Publikováno v:
Earth System Science Data, Vol 15, Pp 4205-4218 (2023)
The French coast of the eastern English Channel (ECC) is classified as a potential eutrophication zone by the Oslo and Paris (OSPAR) Convention and as moderate to poor according to the phytoplankton quality element of the Water Framework Directive (W
Externí odkaz:
https://doaj.org/article/da7365ccdf8f4d42aabcd7c7a07fe994
Autor:
A. Lefebvre, J. Cisneros
Publikováno v:
Earth Surface Dynamics, Vol 11, Pp 575-591 (2023)
Underwater dunes are found in various environments with strong hydrodynamics and movable sediment such as rivers, estuaries and continental shelves. They have a diversity of morphology, ranging from low- to high-angle lee sides and sharp or rounded c
Externí odkaz:
https://doaj.org/article/97e89a0ff1dd4b4c8ffc5aa2d2a09bcb
Autor:
A. Lefebvre, D. Devreker
Publikováno v:
Earth System Science Data, Vol 15, Pp 1077-1092 (2023)
This article describes a 30-year data series produced by the SRN (“Suivi Régional des Nutriments” in French; Regional Nutrients Monitoring Programme) network managed by Ifremer. Since 1992, the SRN network has been analysing phytoplankton specie
Externí odkaz:
https://doaj.org/article/b5b1d759fe3746aa81c5b4091ad20ab9
Autor:
Lefebvre, Martin, Bol, David
Recent advances in artificial intelligence have prompted the search for enhanced algorithms and hardware to support the deployment of machine learning at the edge. More specifically, in the context of the Internet of Things (IoT), vision chips must b
Externí odkaz:
http://arxiv.org/abs/2411.07946
Autor:
Lefebvre, Henri, Subramanyam, Anirudh
We provide a correction to the sufficient conditions under which closed-form expressions for the optimal Lagrange multiplier are provided in arXiv:2112.13138 [math.OC]. We first present a simple counterexample where the original conditions are insuff
Externí odkaz:
http://arxiv.org/abs/2411.04307
State-of-the-art RGB texture synthesis algorithms rely on style distances that are computed through statistics of deep features. These deep features are extracted by classification neural networks that have been trained on large datasets of RGB image
Externí odkaz:
http://arxiv.org/abs/2410.16019
With the rapid development and early industrialization of quantum technologies, it is of great interest to analyze their overall energy consumption before planning for their wide-scale deployments. The evaluation of the total energy requirements of q
Externí odkaz:
http://arxiv.org/abs/2410.10661
Self-Supervised Learning (SSL) has emerged as a promising approach in computer vision, enabling networks to learn meaningful representations from large unlabeled datasets. SSL methods fall into two main categories: instance discrimination and Masked
Externí odkaz:
http://arxiv.org/abs/2410.07442
Detecting small targets in infrared images poses significant challenges in defense applications due to the presence of complex backgrounds and the small size of the targets. Traditional object detection methods often struggle to balance high detectio
Externí odkaz:
http://arxiv.org/abs/2410.07437
Autor:
Johnson, Paul A., Moisset, Jean-David, Gratton, Marianne, Baril, Émile, Plourde, Marc-Antoine, Lefebvre, Mathis, Kerleaux, Marianne, Ayers, Paul W., Cassam-Chenaï, Patrick, De Baerdemacker, Stijn, Van Neck, Dimitri
Wavefunction forms based on products of electron pairs are usually constructed as closed-shell singlets, which is insufficient when the molecular state has a nonzero spin or when the chemistry is determined by $d$- or $f-$electrons. A set of two-elec
Externí odkaz:
http://arxiv.org/abs/2410.01761