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Artigos de revistas sobre o assunto "Intelligence artificielle (IA) embarquée"
EZANNO, Pauline, Sébastien PICAULT, Nathalie WINTER, Gaël BEAUNÉE, Hervé MONOD e Jean-François GUÉGAN. "Intelligence artificielle et santé animale". INRAE Productions Animales 33, n.º 2 (15 de setembro de 2020): 95–108. http://dx.doi.org/10.20870/productions-animales.2020.33.2.3572.
Texto completo da fonteMatuchansky, Claude. "Intelligence clinique et intelligence artificielle". médecine/sciences 35, n.º 10 (outubro de 2019): 797–803. http://dx.doi.org/10.1051/medsci/2019158.
Texto completo da fonteChauvier, Stéphane. "IA : le test de la déférence". Revue de métaphysique et de morale N° 119, n.º 3 (10 de agosto de 2023): 409–25. http://dx.doi.org/10.3917/rmm.233.0409.
Texto completo da fonteBoss, Gilbert, e Maryvonne Longeart. "Philosophic sur ordinateur ou intelligence artificielle". Dialogue 32, n.º 2 (1993): 271–92. http://dx.doi.org/10.1017/s0012217300014438.
Texto completo da fonteCennamo, Ilaria, e Loïc de Faria Pires. "Intelligence artificielle et traduction". FORUM / Revue internationale d’interprétation et de traduction / International Journal of Interpretation and Translation 20, n.º 2 (31 de dezembro de 2022): 333–56. http://dx.doi.org/10.1075/forum.00024.cen.
Texto completo da fonteFoucart, Jean-Michel, Augustin Chavanne e Jérôme Bourriau. "Intelligence artificielle : le futur de l’Orthodontie ?" Revue d'Orthopédie Dento-Faciale 53, n.º 3 (setembro de 2019): 281–94. http://dx.doi.org/10.1051/odf/2019026.
Texto completo da fonteGhoshal, Debalina. "Intelligence artificielle et défense antimissile : quelle perspective pour l’Inde ?" Revue Défense Nationale N° 868, n.º 3 (12 de março de 2024): 105–10. http://dx.doi.org/10.3917/rdna.868.0105.
Texto completo da fonteFranzosi, Marion, Youcef Guechi e Thomas Schmutz. "5 minutes pour apprendre. Intelligence artificielle (IA) : gardons le contrôle". Revue Médicale Suisse 19, n.º 837 (2023): 1474–75. http://dx.doi.org/10.53738/revmed.2023.19.837.1474.
Texto completo da fontePeyrard-Moulard, Martine. "Aide au développement – Intelligence artificielle (IA) – Biais de statu quo". Pour l'Éco N° 52, n.º 5 (1 de junho de 2023): 10–11. http://dx.doi.org/10.3917/poec.052.0010.
Texto completo da fonteQuéméner, Myriam. "Entreprises et intelligence artificielle : quels apports, quels risques ?" Sécurité et stratégie 31, n.º 3 (19 de março de 2024): 54–58. http://dx.doi.org/10.3917/sestr.031.0054.
Texto completo da fonteTeses / dissertações sobre o assunto "Intelligence artificielle (IA) embarquée"
Mainsant, Marion. "Apprentissage continu sous divers scénarios d'arrivée de données : vers des applications robustes et éthiques de l'apprentissage profond". Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALS045.
Texto completo da fonteThe human brain continuously receives information from external stimuli. It then has the ability to adapt to new knowledge while retaining past events. Nowadays, more and more artificial intelligence algorithms aim to learn knowledge in the same way as a human being. They therefore have to be able to adapt to a large variety of data arriving sequentially and available over a limited period of time. However, when a deep learning algorithm learns new data, the knowledge contained in the neural network overlaps old one and the majority of the past information is lost, a phenomenon referred in the literature as catastrophic forgetting. Numerous methods have been proposed to overcome this issue, but as they were focused on providing the best performance, studies have moved away from real-life applications where algorithms need to adapt to changing environments and perform, no matter the type of data arrival. In addition, most of the best state of the art methods are replay methods which retain a small memory of the past and consequently do not preserve data privacy.In this thesis, we propose to explore data arrival scenarios existing in the literature, with the aim of applying them to facial emotion recognition, which is essential for human-robot interactions. To this end, we present Dream Net - Data-Free, a privacy preserving algorithm, able to adapt to a large number of data arrival scenarios without storing any past samples. After demonstrating the robustness of this algorithm compared to existing state-of-the-art methods on standard computer vision databases (Mnist, Cifar-10, Cifar-100 and Imagenet-100), we show that it can also adapt to more complex facial emotion recognition databases. We then propose to embed the algorithm on a Nvidia Jetson nano card creating a demonstrator able to learn and predict emotions in real-time. Finally, we discuss the relevance of our approach for bias mitigation in artificial intelligence, opening up perspectives towards a more ethical AI
Blachon, David. "Reconnaissance de scènes multimodale embarquée". Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM001/document.
Texto completo da fonteContext: This PhD takes place in the contexts of Ambient Intelligence and (Mobile) Context/Scene Awareness. Historically, the project comes from the company ST-Ericsson. The project was depicted as a need to develop and embed a “context server” on the smartphone that would get and provide context information to applications that would require it. One use case was given for illustration: when someone is involved in a meeting and receives a call, then thanks to the understanding of the current scene (meet at work), the smartphone is able to automatically act and, in this case, switch to vibrate mode in order not to disturb the meeting. The main problems consist of i) proposing a definition of what is a scene and what examples of scenes would suit the use case, ii) acquiring a corpus of data to be exploited with machine learning based approaches, and iii) propose algorithmic solutions to the problem of scene recognition.Data collection: After a review of existing databases, it appeared that none fitted the criteria I fixed (long continuous records, multi-sources synchronized records necessarily including audio, relevant labels). Hence, I developed an Android application for collecting data. The application is called RecordMe and has been successfully tested on 10+ devices, running Android 2.3 and 4.0 OS versions. It has been used for 3 different campaigns including the one for scenes. This results in 500+ hours recorded, 25+ volunteers were involved, mostly in Grenoble area but abroad also (Dublin, Singapore, Budapest). The application and the collection protocol both include features for protecting volunteers privacy: for instance, raw audio is not saved, instead MFCCs are saved; sensitive strings (GPS coordinates, device ids) are hashed on the phone.Scene definition: The study of existing works related to the task of scene recognition, along with the analysis of the annotations provided by the volunteers during the data collection, allowed me to propose a definition of a scene. It is defined as a generalisation of a situation, composed of a place and an action performed by one person (the smartphone owner). Examples of scenes include taking a transportation, being involved in a work meeting, walking in the street. The composition allows to get different kinds of information to provide on the current scene. However, the definition is still too generic, and I think that it might be completed with additionnal information, integrated as new elements of the composition.Algorithmics: I have performed experiments involving machine learning techniques, both supervised and unsupervised. The supervised one is about classification. The method is quite standard: find relevant descriptors of the data through the use of an attribute selection method. Then train and test several classifiers (in my case, there were J48 and Random Forest trees ; GMM ; HMM ; and DNN). Also, I have tried a 2-stage system composed of a first step of classifiers trained to identify intermediate concepts and whose predictions are merged in order to estimate the most likely scene. The unsupervised part of the work aimed at extracting information from the data, in an unsupervised way. For this purpose, I applied a bottom-up hierarchical clustering, based on the EM algorithm on acceleration and audio data, taken separately and together. One of the results is the distinction of acceleration into groups based on the amount of agitation
Chamberland, Simon. "Deux investigations en IA : contrôler les déplacements d'un robot mobile et coordonner les décisions d'une IA pour les jeux". Mémoire, Université de Sherbrooke, 2013. http://savoirs.usherbrooke.ca/handle/11143/45.
Texto completo da fonteChamberland, Simon. "Deux investigations en IA : contr??ler les d??placements d'un robot mobile et coordonner les d??cisions d'une IA pour les jeux". Mémoire, Universit?? de Sherbrooke, 2013. http://savoirs.usherbrooke.ca/handle/11143/45.
Texto completo da fonteNabholtz, Franz-Olivier. "Problématisation prospective des stratégies de la singularité". Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCB019.
Texto completo da fonteFrom past world to globalization, from modernity to postmodernity, from the human to the transhuman: - the digital and technological revolution brings out issues that permeate our daily lives beyond even what common sense can imagine. The massification of data, analyzed as the result of a hyper-connectivity, linked to a convergence "big data-artificial intelligence" raises the question of its fair use and distribution between highly voluntary private actors (GAFA) and public institutions for the least outdated, as to the principles of rational efficiency representing one of the characteristics of datas. A predictive characteristic that corresponds to a vital need of states. A human society with specific knowledge of its situation could make rational choices based on predictive scenarios and would no longer behave in the same way and no longer normalize in the same way. If we reject transhumanism in its ideological dimension, we take for granted the conceptual dimensions of the theory of singularity that we problematize in this work by an analysis of information specific to an approach of economic intelligence, even beyond of common thought and consensus inherited from a deductive school of thought that has been affirmed by demonstration and imposed by a form of ideology that exists everywhere, if not in social sciences. Inductive thinking, whose primary characteristic is predictive correlation, would see the development of probabilistic, multidisciplinary, bold and peculiar political science scenarios, the main idea of which would be to detect and anticipate, as predictive medicine (this is what singularity tells us), major societal and political future trends. However, the nature of this work will have to be fully independent. The process of exploiting big data by means of algorithms, outside traditional processes of scientific validation, will be based on a new model, in which the proof of the cause will undoubtedly take on a quantum or synaptic dimension in a near future, analyzed thus, as singular
Ayats, H. Ambre. "Construction de graphes de connaissances à partir de textes avec une intelligence artificielle explicable et centrée-utilisateur·ice". Electronic Thesis or Diss., Université de Rennes (2023-....), 2023. http://www.theses.fr/2023URENS095.
Texto completo da fonteWith recent advances in artificial intelligence, the question of human control has become central. Today, this involves both research into explainability and designs centered around interaction with the user. What's more, with the expansion of the semantic web and automatic natural language processing methods, the task of constructing knowledge graphs from texts has become an important issue. This thesis presents a user-centered system for the construction of knowledge graphs from texts. This thesis presents several contributions. First, we introduce a user-centered workflow for the aforementioned task, having the property of progressively automating the user's actions while leaving them a fine-grained control over the outcome. Next, we present our contributions in the field of formal concept analysis, used to design an explainable instance-based learning module for relation classification. Finally, we present our contributions in the field of relation extraction, and how these fit into the presented workflow
Robert, Gabriel. "MHiCS, une architecture de sélection de l'action motivationnelle et hiérarchique à systèmes de classeurs pour personnages non joueurs adaptatifs". Paris 6, 2005. http://www.theses.fr/2005PA066165.
Texto completo da fonteAfchar, Darius. "Interpretable Music Recommender Systems". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS608.
Texto completo da fonte‘‘Why do they keep recommending me this music track?’’ ‘‘Why did our system recommend these tracks to users?’’ Nowadays, streaming platforms are the most common way to listen to recorded music. Still, music recommendations — at the heart of these platforms — are not an easy feat. Sometimes, both users and engineers may be equally puzzled about the behaviour of a music recommendation system (MRS). MRS have been successfully employed to help explore catalogues that may be as large as tens of millions of music tracks. Built and optimised for accuracy, real-world MRS often end up being quite complex. They may further rely on a range of interconnected modules that, for instance, analyse audio signals, retrieve metadata about albums and artists, collect and aggregate user feedbacks on the music service, and compute item similarities with collaborative filtering. All this complexity hinders the ability to explain recommendations and, more broadly, explain the system. Yet, explanations are essential for users to foster a long-term engagement with a system that they can understand (and forgive), and for system owners to rationalise failures and improve said system. Interpretability may also be needed to check the fairness of a decision or can be framed as a means to control the recommendations better. Moreover, we could also recursively question: Why does an explanation method explain in a certain way? Is this explanation relevant? What could be a better explanation? All these questions relate to the interpretability of MRSs. In the first half of this thesis, we explore the many flavours that interpretability can have in various recommendation tasks. Indeed, since there is not just one recommendation task but many (e.g., sequential recommendation, playlist continuation, artist similarity), as well as many angles through which music may be represented and processed (e.g., metadata, audio signals, embeddings computed from listening patterns), there are as many settings that require specific adjustments to make explanations relevant. A topic like this one can never be exhaustively addressed. This study was guided along some of the mentioned modalities of musical objects: interpreting implicit user logs, item features, audio signals and similarity embeddings. Our contribution includes several novel methods for eXplainable Artificial Intelligence (XAI) and several theoretical results, shedding new light on our understanding of past methods. Nevertheless, similar to how recommendations may not be interpretable, explanations about them may themselves lack interpretability and justifications. Therefore, in the second half of this thesis, we found it essential to take a step back from the rationale of ML and try to address a (perhaps surprisingly) understudied question in XAI: ‘‘What is interpretability?’’ Introducing concepts from philosophy and social sciences, we stress that there is a misalignment in the way explanations from XAI are generated and unfold versus how humans actually explain. We highlight that current research tends to rely too much on intuitions or hasty reduction of complex realities into convenient mathematical terms, which leads to the canonisation of assumptions into questionable standards (e.g., sparsity entails interpretability). We have treated this part as a comprehensive tutorial addressed to ML researchers to better ground their knowledge of explanations with a precise vocabulary and a broader perspective. We provide practical advice and highlight less popular branches of XAI better aligned with human cognition. Of course, we also reflect back and recontextualise our methods proposed in the previous part. Overall, this enables us to formulate some perspective for our field of XAI as a whole, including its more critical and promising next steps as well as its shortcomings to overcome
Dubus, Georges. "Transformation de programmes logiques : application à la personnalisation et à la personnification d’agents". Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0017/document.
Texto completo da fonteThis thesis deals with personalization and personification of rational agents within the framework of web applications. Personalization and personification techniques are more and more used to answer the needs of users. Most of those techniques are based on reasoning tools that come from the artificial inteligence field. However, those techniques are usually used in an ad-hoc way for each application. The approach of this thesis is to consider personaliaation and personification as two instances of alteration of behaviour, and to study the alteration of the behaviours of rational agents. The main contributions are WAIG, a formalism for the expression of web applications based on the agent programming language Golog, and PAGE, a formal framework for the manipulation and the alteration of Golog agent programs, which allow to transform an agent automatically following a given criterion. Those contributions are illustrated by concrete scenarios from the fields of personalization and personification
Wang, Olivier. "Adaptive Rules Model : Statistical Learning for Rule-Based Systems". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX037/document.
Texto completo da fonteBusiness Rules (BRs) are a commonly used tool in industry for the automation of repetitive decisions. The emerging problem of adapting existing sets of BRs to an ever-changing environment is the motivation for this thesis. Existing Supervised Machine Learning techniques can be used when the adaptation is done knowing in detail which is the correct decision for each circumstance. However, there is currently no algorithm, theoretical or practical, which can solve this problem when the known information is statistical in nature, as is the case for a bank wishing to control the proportion of loan requests its automated decision service forwards to human experts. We study the specific learning problem where the aim is to adjust the BRs so that the decisions are close to a given average value.To do so, we consider sets of Business Rules as programs. After formalizing some definitions and notations in Chapter 2, the BR programming language defined this way is studied in Chapter 3, which proves that there exists no algorithm to learn Business Rules with a statistical goal in the general case. We then restrain the scope to two common cases where BRs are limited in some way: the Iteration Bounded case in which no matter the input, the number of rules executed when taking the decision is less than a given bound; and the Linear Iteration Bounded case in which rules are also all written in Linear form. In those two cases, we later produce a learning algorithm based on Mathematical Programming which can solve this problem. We briefly extend this theory and algorithm to other statistical goal learning problems in Chapter 5, before presenting the experimental results of this thesis in Chapter 6. The last includes a proof of concept to automate the main part of the learning algorithm which does not consist in solving a Mathematical Programming problem, as well as some experimental evidence of the computational complexity of the algorithm
Livros sobre o assunto "Intelligence artificielle (IA) embarquée"
Conférence européenne sur les techniques et les applications de l'intelligence artificielle en milieu industriel et de service (2nd 1990 Paris, France). Convention IA 90: Actes de la 2e Conférence européenne sur les techniques et les applications de l'intelligence artificielle en milieu industriel et de service, 15-18 janvier 1990, Paris. Paris: Hermès, 1989.
Encontre o texto completo da fonteConférence européenne sur les techniques et les applications de l'intelligence artificielle en milieu industriel et de service. (1st 1989 Paris, France). Convention IA 89: Actes de la 1e Conférence européenne sur les techniques et les applications de l'intelligence artificielle en milieu industriel et de service, 23-27 janvier 1989, Porte de Versailles, Paris. Paris: Hermès, 1989.
Encontre o texto completo da fonteTélémédecine Automatisée Par l'IA - une Nouvelle Méthode de Suivi à Distance des Patients: Intelligence Artificielle/augmentée Distribuée - IA - l'avenir des Soins de Santé. Independently Published, 2021.
Encontre o texto completo da fonteConvention IA 90: Actes de la 2e Conference europeenne sur les techniques et les applications de l'intelligence artificielle en milieu industriel et de service, 15-18 janvier 1990, Paris. Hermes, 1990.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Intelligence artificielle (IA) embarquée"
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.
Texto completo da fontePIATTI, Marie-Christine. "Demain, quelles IA pour quelle humanité ?" In Intelligence(s) artificielle(s) et Vulnérabilité(s) : kaléidoscope, 45–56. Editions des archives contemporaines, 2020. http://dx.doi.org/10.17184/eac.3634.
Texto completo da fontePULIDO, Belarmino, Carlos J. ALONSO-GONZÁLEZ e Anibal BREGON. "Approche par intelligence artificielle du diagnostic basé sur les modèles". In Diagnostic et commande à tolérance de fautes 1, 235–69. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9058.ch6.
Texto completo da fonteBOUCAUD, Pascale. "Protection de la liberté et de la fragilité de la personne face au robot". In Intelligence(s) artificielle(s) et Vulnérabilité(s) : kaléidoscope, 137–48. Editions des archives contemporaines, 2020. http://dx.doi.org/10.17184/eac.3642.
Texto completo da fonteDUBOIS, Didier, Henri PRADE e Claudette TESTEMALE. "WEIGHTED FUZZY PATTERN MATCHING**This work is supported by the “Programme de Recherche Concertée: Intelligence Artificielle” (PRC-IA), sponsored by MRT and CNRS, France." In Readings in Fuzzy Sets for Intelligent Systems, 676–85. Elsevier, 1993. http://dx.doi.org/10.1016/b978-1-4832-1450-4.50073-0.
Texto completo da fonteRelatórios de organizações sobre o assunto "Intelligence artificielle (IA) embarquée"
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, setembro de 2020. http://dx.doi.org/10.61737/zhxd1856.
Texto completo da fonteMörch, Carl-Maria, Pascale Lehoux, Marc-Antoine Dilhac, Catherine Régis e Xavier Dionne. Recommandations pratiques pour une utilisation responsable de l’intelligence artificielle en santé mentale en contexte de pandémie. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, dezembro de 2020. http://dx.doi.org/10.61737/mqaf7428.
Texto completo da fonte