Zobrazeno 1 - 10
of 189
pro vyhledávání: '"Canevet, P."'
Autor:
Granados-Miralles, Cecilia, Saura-Múzquiz, Matilde, Andersen, Henrik L., Quesada, Adrián, Ahlburg, Jakob V., Dippel, Ann-Christin, Canévet, Emmanuel, Christensen, Mogens
Publikováno v:
ACS Appl. Nano Mater. 1 (2018) 3693-3704
During the past decade, CoFe2O4 (hard)/Co-Fe alloy (soft) magnetic nanocomposites have been routinely prepared by partial reduction of CoFe2O4 nanoparticles. Monoxide (i.e., FeO or CoO) has often been detected as a byproduct of the reduction, althoug
Externí odkaz:
http://arxiv.org/abs/2309.13729
We propose to leverage recent advances in reliable 2D pose estimation with Convolutional Neural Networks (CNN) to estimate the 3D pose of people from depth images in multi-person Human-Robot Interaction (HRI) scenarios. Our method is based on the obs
Externí odkaz:
http://arxiv.org/abs/2011.05010
Autor:
Chillal, S., Islam, A. T. M. N, Luetkens, H., Canévet, E., Skourski, Y., Khalyavin, D., Lake, B.
Publikováno v:
Phys. Rev. B 102, 224424 (2020)
SrCuTe$_2$O$_6$ consists of a 3-dimensional arrangement of spin-$\frac{1}{2}$ Cu$^{2+}$ ions. The 1st, 2nd and 3rd neighbor interactions respectively couple Cu$^{2+}$ moments into a network of isolated triangles, a highly frustrated hyperkagome latti
Externí odkaz:
http://arxiv.org/abs/2008.02199
Akademický článek
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Akademický článek
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Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI settings. Accurate methods have been proposed recently, but they usually
Externí odkaz:
http://arxiv.org/abs/1912.00711
Publikováno v:
2018 IEEE International Conference on Intelligent Robots and Systems, Madrid, Spain
We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human Robot Interaction (HRI) scenarios. Our hypothesis is that depth images
Externí odkaz:
http://arxiv.org/abs/1910.13911
Autor:
Foster, Mary Ellen, Craenen, Bart, Deshmukh, Amol, Lemon, Oliver, Bastianelli, Emanuele, Dondrup, Christian, Papaioannou, Ioannis, Vanzo, Andrea, Odobez, Jean-Marc, Canévet, Olivier, Cao, Yuanzhouhan, He, Weipeng, Martínez-González, Angel, Motlicek, Petr, Siegfried, Rémy, Alami, Rachid, Belhassein, Kathleen, Buisan, Guilhem, Clodic, Aurélie, Mayima, Amandine, Sallami, Yoan, Sarthou, Guillaume, Singamaneni, Phani-Teja, Waldhart, Jules, Mazel, Alexandre, Caniot, Maxime, Niemelä, Marketta, Heikkilä, Päivi, Lammi, Hanna, Tammela, Antti
In the EU-funded MuMMER project, we have developed a social robot designed to interact naturally and flexibly with users in public spaces such as a shopping mall. We present the latest version of the robot system developed during the project. This sy
Externí odkaz:
http://arxiv.org/abs/1909.06749
Autor:
Ruellan, B., Cam, Jean-Benoit Le, Robin, E., Jeanneau, I., Canevet, F., Mauvoisin, G., Loison, D.
Publikováno v:
SEM Annual conference, Jun 2019, Reno, United States
Natural rubber (NR) is the most commonly used elastomer in the automotive industry thanks to its outstanding fatigue resistance. Strain-induced crystallization (SIC) is found to play a role of paramount importance in the great crack growth resistance
Externí odkaz:
http://arxiv.org/abs/1907.02688
Autor:
Tayeb, A, Cam, Jean-Benoit Le, Grédiac, M., Toussaint, E., Canevet, F., Robin, E., Balandraud, X.
Publikováno v:
SEM Annual conference, Jun 2019, Reno, United States
In this study, the Virtual Fields Method (VFM) is applied to identify constitutive parameters of hyperelastic models from a heterogeneous test. Digital image correlation (DIC) was used to estimate the displacement and strain fields required by the id
Externí odkaz:
http://arxiv.org/abs/1907.02687