Letteratura scientifica selezionata sul tema "Hardware pour l'intelligence artificielle"
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Articoli di riviste sul tema "Hardware pour l'intelligence artificielle":
Arnold, Madeleine. "La sémiotique : un instrument pour la représentation des connaissances en intelligence artificielle". Études littéraires 21, n. 3 (12 aprile 2005): 81–90. http://dx.doi.org/10.7202/500872ar.
Selz, Marion. "Apports de l'intelligence artificielle pour l'historien". Le médiéviste et l'ordinateur 1, n. 1 (1990): 173–78. http://dx.doi.org/10.3406/medio.1990.1264.
Brahmi, Halima, Saïda Belouali, Yves Demazeau, Toumi Bouchentouf e Nissrine Hassini Alaoui. "Vers un référentiel universel pour un usage éthique de l’intelligence artificielle". East African Journal of Information Technology 6, n. 1 (24 maggio 2023): 91–106. http://dx.doi.org/10.37284/eajit.6.1.1226.
Longeart, Maryvonne. "Intelligence et intentionalité. Critique de l'argument de Searle contre l'intelligence artificielle". Dialogue 30, n. 1-2 (1991): 85–102. http://dx.doi.org/10.1017/s0012217300013342.
Djeriri, Youcef, e Zinelaabidine Boudjema. "Commande robuste par la logique floue et les réseaux de neurones artificiels de la GADA : étude comparative". Journal of Renewable Energies 20, n. 1 (12 ottobre 2023): 147–60. http://dx.doi.org/10.54966/jreen.v20i1.616.
El Ouidani, Rania, Ahmed Outouzzalt e Mustapha Bengrich. "Étude bibliométrique sur la prédiction de la défaillance des entreprises par les big data intelligents". International Journal of Financial Studies, Economics and Management 2, n. 2 (22 maggio 2023): 17–41. http://dx.doi.org/10.61549/ijfsem.v2i2.112.
Cabanat, Alice, e Caio Padovan. "PSYCHANALYSE DE L'INTELLIGENCE". Eleuthería - Revista do Curso de Filosofia da UFMS 7, n. 13 (30 settembre 2022): 11–22. http://dx.doi.org/10.55028/eleu.v7i13.15530.
KIM, Hee-Kyung. "Réflexions sur l'avenir de la didactique du français langues étrangères: sous la didactique des langues étrangères face à l'évolution des technologies". Societe d'Etudes Franco-Coreennes 101 (30 aprile 2023): 129–54. http://dx.doi.org/10.18812/refc.2023.101.129.
KIM, Hee-Kyung. "Réflexions sur l'avenir de la didactique du français langues étrangères: sous la didactique des langues étrangères face à l'évolution des technologies". Societe d'Etudes Franco-Coreennes 101 (30 aprile 2023): 129–54. http://dx.doi.org/10.18812/refc.2023.101.129.
Contu, S., R. Schiappa, T. Villard, A. Bonnifay, Y. Chateau, E. Seutin, G. Baudin e E. Chamorey. "P32 - AUTORECIST : utilisation de l'intelligence artificielle pour prédire la réponse RECIST". Journal of Epidemiology and Population Health 72 (maggio 2024): 202472. http://dx.doi.org/10.1016/j.jeph.2024.202472.
Tesi sul tema "Hardware pour l'intelligence artificielle":
Janzakova, Kamila. "Développement de dendrites polymères organiques en 3D comme dispositif neuromorphique". Electronic Thesis or Diss., Université de Lille (2022-....), 2023. http://www.theses.fr/2023ULILN017.
Neuromorphic technologies is a promising direction for development of more advanced and energy-efficient computing. They aim to replicate attractive brain features such as high computational efficiency at low power consumption on a software and hardware level. At the moment, brain-inspired software implementations (such as ANN and SNN) have already shown their successful application for different types of tasks (image and speech recognition). However, to benefit more from the brain-like algorithms, one may combine them with appropriate hardware that would also rely on brain-like architecture and processes and thus complement them. Neuromorphic engineering has already shown the utilization of solid-state electronics (CMOS circuits, memristor) for the development of brain-inspired devices. Nevertheless, these implementations are fabricated through top-down methods. In contrast, brain computing relies on bottom-up processes such as interconnectivity between cells and the formation of neural communication pathways.In the light of mentioned above, this work reports on the development of programmable 3D organic neuromorphic devices, which, unlike most current neuromorphic technologies, can be created in a bottom-up manner. This allows bringing neuromorphic technologies closer to the level of brain programming, where necessary neural paths are established only on the need.First, we found out that PEDOT:PSS based 3D interconnections can be formed by means of AC-bipolar electropolymerization and that they are capable of mimicking the growth of neural cells. By tuning individually the parameters of the waveform (peak amplitude voltage -VP, frequency - f, duty cycle - dc and offset voltage - Voff), a wide range of dendrite-like structures was observed with various branching degrees, volumes, surface areas, asymmetry of formation, and even growth dynamics.Next, it was discovered that dendritic morphologies obtained at various frequencies are conductive. Moreover, each structure exhibits an individual conductance value that can be interpreted as synaptic weight. More importantly, the ability of dendrites to function as OECT was revealed. Different dendrites exhibited different performances as OECT. Further, the ability of PEDOT:PSS dendrites to change their conductivity in response to gate voltage was used to mimic brain memory functions (short-term plasticity -STP and long-term plasticity -LTP). STP responses varied depending on the dendritic structure. Moreover, emulation of LTP was demonstrated not only by means of an Ag/AgCl gate wire but as well by means of a self-developed polymer dendritic gate.Finally, structural plasticity was demonstrated through dendritic growth, where the weight of the final connection is governed according to Hebbian learning rules (spike-timing-dependent plasticity - STDP and spike-rate-dependent plasticity - SRDP). Using both approaches, a variety of dendritic topologies with programmable conductance states (i.e., synaptic weight) and various dynamics of growth have been observed. Eventually, using the same dendritic structural plasticity, more complex brain features such as associative learning and classification tasks were emulated.Additionally, future perspectives of such technologies based on self-propagating polymer dendritic objects were discussed
Voyiatzis, Konstantinos. "Utilisation de l'intelligence artificielle pour les problèmes d'ordonnancement". Paris 9, 1987. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1987PA090102.
The present work concerns the scheduling of the products in a production system from "jobshop" type. This problem is a combinatorial problem and has an incompatible solution with the "real time" contraint. We demonstrate in which way this approach "artificial intelligence" can conduct to an acceptable scheduling in real time. The first chapter presents the structure of the artificial memory we use. The second one tells us an example of utilization on this approach. The appendix i remains the basis of production managment. The appendix ii gives us the basis of the automatic classification used in severals parts of this work. And the appendix iii, contains the software of simulation written in slam
Voyiatzis, Konstantinos. "Utilisation de l'intelligence artificielle pour les problèmes d'ordonnancement". Grenoble 2 : ANRT, 1987. http://catalogue.bnf.fr/ark:/12148/cb376106812.
Neggaz, Mohamed Ayoub. "Accélérateurs Matériels pour l'Intelligence Artificielle. Etude de Cas : Voitures Autonomes". Thesis, Valenciennes, Université Polytechnique Hauts-de-France, 2020. http://www.theses.fr/2020UPHF0017.
Since the early days of the DARPA challenge, the design of self-driving cars is catching increasing interest. This interest is growing even more with the recent successes of Machine Learning algorithms in perception tasks. While the accuracy of thesealgorithms is irreplaceable, it is very challenging to harness their potential. Realtime constraints as well as reliability issues heighten the burden of designing efficient platforms.We discuss the different implementations and optimization techniques in this work. We tackle the problem of these accelerators from two perspectives: performance and reliability. We propose two acceleration techniques that optimize time and resource usage. On reliability, we study the resilience of Machine Learning algorithms. We propose a tool that gives insights whether these algorithms are reliable enough forsafety critical systems or not. The Resistive Associative Processor accelerator achieves high performance due to its in-memory design which remedies the memory bottleneck present in most Machine Learning algorithms. As for the constant multiplication approach, we opened the door for a new category of optimizations by designing instance specific accelerators. The obtained results outperforms the most recent techniques in terms of execution time and resource usage. Combined with the reliability study we conducted, safety-critical systems can profit from these accelerators without compromising its security
Gaïti, Dominique. "L'utilisation des techniques de l'intelligence artificielle pour la gestion des reseaux". Paris 6, 1991. http://www.theses.fr/1991PA066493.
Claes, Gérard. "Contribution à l'application de l'intelligence artificielle pour l'enseignement assisté par ordinateur". Paris 11, 1988. http://www.theses.fr/1988PA112412.
Claes, Gérard. "Contribution à l'application de l'intelligence artificielle pour l'enseignement assisté par ordinateur". Grenoble 2 : ANRT, 1988. http://catalogue.bnf.fr/ark:/12148/cb376127000.
Levasseur, Yan. "Techniques de l'intelligence artificielle pour la classification d'objets biologiques dans des images bidimensionnelles". Mémoire, École de technologie supérieure, 2008. http://espace.etsmtl.ca/115/1/LEVASSEUR_Yan.pdf.
CHERIE, NABIL. "Utilisation des techniques de l'intelligence artificielle pour la modelisation du mouvement d'objets animes". Paris 11, 1991. http://www.theses.fr/1991PA112075.
Panaïotis, Thelma. "Distribution du plancton à diverses échelles : apport de l'intelligence artificielle pour l'écologie planctonique". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS155.
As the basis of oceanic food webs and a key component of the biological carbon pump, planktonic organisms play major roles in the oceans. However, their small-scale distribution − governed by biotic interactions between organisms and interactions with the physico-chemical properties of the water masses in their immediate environment − are poorly described in situ due to the lack of suitable observation tools. New instruments performing high resolution imaging in situ in combination with machine learning algorithms to process the large amount of collected data now allows us to address these scales. The first part of this work focuses on the methodological development of two automated pipelines based on artificial intelligence. These pipelines allowed to efficiently detect planktonic organisms within raw images, and classify them into taxonomical or morphological categories. Then, in a second part, numerical ecology tools have been applied to study plankton distribution at different scales, using three different in situ imaging datasets. First, we investigated the link between plankton community and environmental conditions at the global scale. Then, we resolved plankton and particle distribution across a mesoscale front, and highlighted contrasted periods during the spring bloom. Finally, leveraging high frequency in situ imaging data, we investigated the fine-scale distribution and preferential position of Rhizaria, a group of understudied, fragile protists, some of which are mixotrophic. Overall, these studies demonstrate the effectiveness of in situ imaging combined with artificial intelligence to understand biophysical interactions in plankton and distribution patterns at small-scale
Libri sul tema "Hardware pour l'intelligence artificielle":
Gochet, Paul, Pascal Gribomont e André Thayse. Méthodes pour l'intelligence artificielle. Paris: Hermès, 2000.
Turner, Raymond. Logiques pour l'intelligence artificielle. Paris: Masson, 1986.
Kaufmann, A. Nouvelles logiques pour l'intelligence artificielle. Paris: Hemès, 1987.
Antomarchi, Florence. Pense-- machine: Pour comprendre l'intelligence artificielle. Paris: Centre d'études des systèmes et des technologies avancées, 1986.
Bratko, Ivan. Programmation en Prolog pour l'intelligence artificielle. Paris: InterEditions, 1988.
Bouché, Marcel B. Pour un renouveau dans l'environnement: De l'antiscience à l'intelligence artificielle des systèmes complexes. Paris: L'Harmattan, 2012.
Bestougeff, Hélène. Outils logiques pour le traitement du temps: De la linguistique à l'intelligence artificielle. Paris: Masson, 1989.
Meneceur, Yannick. L'intelligence artificielle en procès: Plaidoyer pour une réglementation internationale et européenne. BRUYLANT, 2020.
Wirtz, Jochen, Pascal Bornet e Ian Barkin. Automatisation Intelligente: Apprenez Comment Utiliser l'intelligence Artificielle Pour Stimuler les Entreprises et Rendre Notre Monde Plus Humain. Independently Published, 2020.
Capitoli di libri sul tema "Hardware pour l'intelligence artificielle":
"2. Avec l’intelligence artificielle générale pour Graal". In L'intelligence artificielle, 33–68. EDP Sciences, 2021. http://dx.doi.org/10.1051/978-2-7598-2580-6.c004.
BAILLARGEAT, Dominique. "Intelligence Artificielle et villes intelligentes". In Algorithmes et Société, 37–46. Editions des archives contemporaines, 2021. http://dx.doi.org/10.17184/eac.4544.
Duguet, Anne-Marie. "Place du numérique et de l’intelligence artificielle dans l’activité médicale. Éléments pour une réflexion commune entre médecins et entreprises". In L'entreprise et l'intelligence artificielle - Les réponses du droit, 403–17. Presses de l’Université Toulouse 1 Capitole, 2022. http://dx.doi.org/10.4000/books.putc.15470.
RAVEL, Guillaume. "Algorithmes et recrutement". In Algorithmes et Société, 79–88. Editions des archives contemporaines, 2021. http://dx.doi.org/10.17184/eac.4558.
PICHENOT, Évelyne. "Société civile européenne et enjeux des algorithmes". In Algorithmes et Société, 141–54. Editions des archives contemporaines, 2021. http://dx.doi.org/10.17184/eac.4621.
Atti di convegni sul tema "Hardware pour l'intelligence artificielle":
ORLIANGES, Jean-Christophe, Younes El Moustakime, Aurelian Crunteanu STANESCU, Ricardo Carrizales Juarez e Oihan Allegret. "Retour vers le perceptron - fabrication d’un neurone synthétique à base de composants électroniques analogiques simples". In Les journées de l'interdisciplinarité 2023. Limoges: Université de Limoges, 2024. http://dx.doi.org/10.25965/lji.761.
Rapporti di organizzazioni sul tema "Hardware pour l'intelligence artificielle":
Audet, René, e Tom Lebrun. Livre blanc : L'intelligence artificielle et le monde du livre. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, settembre 2020. http://dx.doi.org/10.61737/zhxd1856.
Dilhac, Marc-Antoine, Vincent Mai, Carl-Maria Mörch, Pauline Noiseau e Nathalie Voarino. Penser l’intelligence artificielle responsable : un guide de délibération. Observatoire international sur les impacts sociétaux de l'IA et du numérique, marzo 2020. http://dx.doi.org/10.61737/nicj7555.