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24 results on '"Brousse, Olivier"'

2. Towards Autonomous Scalable Integrated Systems

Author

Benoit, Pascal, Sassatelli, Gilles, Maurine, Philippe, Torres, Lionel, Azemard, Nadine, Robert, Michel, Clermidy, Fabien, Belleville, Marc, Puschini, Diego, Rebaud, Bettina, Brousse, Olivier, Almeida, Gabriel Marchesan, Nicolescu, Gabriela, editor, O'Connor, Ian, editor, and Piguet, Christian, editor

Published
2012
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4. The Perplexus Programming Framework: Combining Bio-inspiration and Agent-Oriented Programming for the Simulation of Large Scale Complex Systems

Author

Brousse, Olivier, Sassatelli, Gilles, Gil, Thierry, Robert, Michel, Grize, François, Sanchez, Eduardo, Upegui, Andrés, Thoma, Yann, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Hornby, Gregory S., editor, Sekanina, Lukáš, editor, and Haddow, Pauline C., editor

Published
2008
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6. Influence of carrier gas on microwave gas response : Detection of ammonia in air / argon

Author

Rossignol Jerome, Brousse Olivier, Grzelak Ludmilla, Paindavoine Michel, Lasserre Alexis, Pribetich Pierre, and Stuerga Didier

Subjects
Argon, Materials science, business.industry, chemistry.chemical_element, Temperature measurement, Microstrip, Ammonia, chemistry.chemical_compound, Petrochemical, Adsorption, chemistry, Desorption, Optoelectronics, business, Microwave
Abstract

The impact of carrier gas species on the response of microwave gas sensor at room temperature is estimated in this paper. The microwave transduction is a good candidate for embedded sensing devoted to Internet of Things. The sensing characteristics are investigated (drift of the baseline, reversibility, recovery time, kinetics) with air and argon flow. Ammonia is chosen for the detection in a wide range of concentration [20 -500 ppm] according to the various cases in agri-food, petrochemical and freezing applications. The substrate is flexible (Duroid). The used sensitive material is TiO 2 super-substrate on a microstrip spiral resonator. The pattern is a trapezoidal spiral working in wide-band of frequencies [1-8 GHz]. In these conditions of sensing, the kinetic of adsorption and desorption and its order are evaluated. Sensing mechanisms are discussed.

Published
2020

7. Virtual memories and Massive Generalization in Connectionist Combinatorial Learning

Author

Brousse, Olivier and Smolensky, Paul

Abstract

W e report a series of experiments on connectionist learning that addresses a particularly pressing set of objections to Ihe plausibility of connectionist learning as a model of human learning. Connectionist models have typically suffered from rather severe problems of inadequate generalization(where generalizations are significantly fewer than training inputs) and interference of newly learned items with previously learned items. Taking a cue from the domains in which human learning dramatically overcomes such problems, we sec that indeed connectionist learning can escape these problems in combinatorially structured domains. In the simple combinatorial domain of letter sequences, w e find that a basic connectionist learning model trained on 50 6-letter sequences can correctly generalize to about 10,000 novel sequences. W e also discover that the model exhibits over 1,000,000 virtual memories: new items which, although not correctly generalized, can be learned in a few presentations while leaving performance on the previously learned items intact.W e conclude that connectionist learning is not as hannful to the empiricist position as previously reported experiments might suggest.

Published
1989

8. Smart NeuroCam with High Level Configuration Tool

Author

Brousse , Olivier, Camenen , Guillaume, Dutrieux , Axel, Joly , Clément, Paindavoine , Michel, Globalsensing Technologies ( GST ), Laboratoire d'Etude de l'Apprentissage et du Développement [Dijon] ( LEAD ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), IEEE (Institute of Electrical and Electronics Engineers), Globalsensing Technologies (GST), Laboratoire d'Etude de l'Apprentissage et du Développement [Dijon] (LEAD), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), and université de Bourgogne, LEAD

Subjects
[SPI.AUTO] Engineering Sciences [physics]/Automatic, Smart image sensor, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [ SPI.AUTO ] Engineering Sciences [physics]/Automatic, Hardware_INTEGRATEDCIRCUITS, ComputingMilieux_MISCELLANEOUS, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Hardware_LOGICDESIGN
Abstract

Thème de la conférence : New Circuits and Systems; International audience

Published
2017

9. Dispositif d'extraction d'informations à partir d'une image

Author

boisard , olivier, Brousse , Olivier, Paindavoine , Michel, Laboratoire d'Etude de l'Apprentissage et du Développement [Dijon] (LEAD), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Globalsensing Technologies (GST), Laboratoire d'Etude de l'Apprentissage et du Développement [Dijon] ( LEAD ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Globalsensing Technologies ( GST ), and université de Bourgogne, LEAD

Subjects
[ INFO ] Computer Science [cs], [INFO]Computer Science [cs], Extraction d'informations, [INFO] Computer Science [cs], Informatique
Abstract

L'invention concerne un dispositif d'extraction d'informations (10) à partir d'une image (12), le dispositif comportant une alternance de deux couches simples (S1, S2) et de deux couches complexes (C1, C2), -la première couche simple (S1) comportant un banc de filtres (15) qui diffèrent par leurs tailles et/ou leurs orientations, chaque filtre (15) étant configuré pour filtrer l'image d'entrée (12, 14), -la première couche simple (S1) intégrant des filtres (15) dont chaque coefficient (16) est codé sur un nombre de bits inférieur ou égal à 8 bits.

Published
2017

10. DAMAV project for vineyard disease detection by UAV imagery

Author

Al-Saddik, Hania, Simon, Jean-Claude, Brousse, Olivier, Cointault, Frédéric, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), GlobalSensing Technologies, Université de Lausanne, Université de Bourgogne (UB), Agroécologie [Dijon], Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC), Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre National de la Recherche Scientifique ( CNRS ), Université de Bourgogne ( UB ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté ( UBFC ), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and ProdInra, Archive Ouverte

Subjects
[SDV] Life Sciences [q-bio], [ SDV ] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract

AgrosupBAPGEAPSI; DAMAV project for vineyard disease detection by UAV imagery . CIRG-AgEng 2016, International Conférence on Agricultural Engineering, Automation, Environment and Food Safety

Published
2016

11. Solution de détection des maladies de la vigne par imagerie de drone. Diagnostic et réduction des pesticides à la parcelle

Author

Al Saddik, Hania, Han, Simeng, Simon, Jean-Claude, Brousse, Olivier, Zunino, Eric, Salon, Christophe, Cointault, Frédéric, ProdInra, Archive Ouverte, Agroécologie [Dijon], Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC), GST Headquarter Research & Development Technical (GST), NOVADEM, Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté ( UBFC ), and GST Headquarter Research & Development Technical ( GST )

Subjects
réduction pesticides, [SDV] Life Sciences [q-bio], [ SDV ] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], imagerie aérienne, diagnostic, détection des maladies, drone, vigne
Abstract

ARTICLE A NE PAS DIFFUSEREAGEAPSIAgrosupCT1; Solution de détection des maladies de la vigne par imagerie de drone. Diagnostic et réduction des pesticides à la parcelle

Published
2016

13. Toward nano-device image processing: a neuro-inspired learning approach

Author

Paindavoine, Michel, Brousse, Olivier, Gamrat, Christian, Laboratoire d'Etude de l'Apprentissage et du Développement [Dijon] (LEAD), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Calculateurs Embarqués et Image (LCEI), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), and université de Bourgogne, LEAD

Subjects
[SCCO.PSYC] Cognitive science/Psychology, [SCCO.PSYC]Cognitive science/Psychology
Abstract

National audience; As nano-scale devices such as OG-CNTFETs are under studies and may be used in a near future, we choose to investigate in which application domain such components may be of the most interest. In this paper we present how neural networks can be used to implement functions on nano-scale components. This method has been tested in the image processing application field.

Published
2010

16. Distributed Pervasive Phylogenetic Application using a Bio-Inspired Agent Framework

Author

Brousse, Olivier, Sassatelli, Gilles, Gil, Thierry, Grize, François, Robert, Michel, Torres, Lionel, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Conception et Test de Systèmes MICroélectroniques (SysMIC), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Université de Lausanne (UNIL), and Torres, Lionel

Subjects
[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2008

17. Perplexus Project

Author

Brousse, Olivier, Sassatelli, Gilles, Gil, Thierry, Robert, Michel, Torres, Lionel, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Conception et Test de Systèmes MICroélectroniques (SysMIC), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2007

24. A Mobile Computing Framework for Pervasive Adaptive Platforms.

Author

Brousse, Olivier, Guillot, Jérémie, Sassatelli, Gilles, Gil, Thierry, Grize, François, and Robert, Michel

Subjects
*MOBILE computing, *COMPUTER programming, *APPLICATION software, *COMPUTER input-output equipment, *COMPUTATIONAL complexity, *MOBILE agent systems
Abstract

Ubiquitous computing is now the new computing trend, such systems that interact with their environment require self adaptability. Bio inspiration is a natural candidate to provide the capability to handle complex and changing scenarios. This paper presents a programming framework dedicated to pervasive platforms programming. This bio inspired and agent oriented framework has been developed within the frame of the PERPLEXUS European project that is intended to provide support for bio inspiration-driven system adaptability. This framework enables the platform to adapt itself to application requirements at high-level while using hardware acceleration at node level. The resulting programming solution has been used to program three collaborative robotic applications in which robots learn tasks and evolve for achieving a better adaptation to their environment. [ABSTRACT FROM AUTHOR]

Published
2012
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