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Relevant bibliographies by topics / Intelligent Edge Networks / Dissertations / Theses

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Dissertations / Theses on the topic 'Intelligent Edge Networks'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Mestoukirdi, Mohamad. "Reliable and Communication-Efficient Federated Learning for Future Intelligent Edge Networks." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS432.

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Dans le domaine des futurs réseaux sans fil 6G, l'intégration de la périphérie intelligente grâce à l'avènement de l'IA représente un bond en avant considérable, promettant des avancées révolutionnaires en matière de communication sans fil. Cette intégration favorise une synergie harmonieuse, capitalisant sur le potentiel collectif de ces technologies transformatrices. Au cœur de cette intégration se trouve le rôle de l'apprentissage fédéré, un paradigme d'apprentissage décentralisé qui préserve la confidentialité des données tout en exploitant l'intelligence collective des appareils interconn

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2

Sigwele, Tshiamo, Yim Fun Hu, M. Ali, Jiachen Hou, M. Susanto, and H. Fitriawan. "An intelligent edge computing based semantic gateway for healthcare systems interoperability and collaboration." IEEE, 2018. http://hdl.handle.net/10454/17552.

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Yes<br>The use of Information and Communications Technology (ICTs) in healthcare has the potential of minimizing medical errors, reducing healthcare cost and improving collaboration between healthcare systems which can dramatically improve the healthcare service quality. However interoperability within different healthcare systems (clinics/hospitals/pharmacies) remains an issue of further research due to a lack of collaboration and exchange of healthcare information. To solve this problem, cross healthcare system collaboration is required. This paper proposes a conceptual semantic based health

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3

Friji, Hamdi. "Graph neural network-based intrusion detection for secure edge networks." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAS030.

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Face à l'escalade de la complexité et à la fréquence des cyberattaques, cette thèse propose des approches innovantes pour la détection d'intrusion dans les réseaux, en exploitant les capacités avancées des réseaux de neurones en graphe (Graph Neural Networks, GNNs) et de nouvelles représentations sous forme de graphes. Nous commençons par une analyse critique des jeux de données et des représentations de réseaux actuels, en abordant des questions clés sur leur efficacité. Nous introduisons une nouvelle représentation des flux de communication sous forme de graphes, offrant une plus grande robu

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4

Hasanaj, Enis, Albert Aveler, and William Söder. "Cooperative edge deepfake detection." Thesis, Jönköping University, JTH, Avdelningen för datateknik och informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53790.

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Deepfakes are an emerging problem in social media and for celebrities and political profiles, it can be devastating to their reputation if the technology ends up in the wrong hands. Creating deepfakes is becoming increasingly easy. Attempts have been made at detecting whether a face in an image is real or not but training these machine learning models can be a very time-consuming process. This research proposes a solution to training deepfake detection models cooperatively on the edge. This is done in order to evaluate if the training process, among other things, can be made more efficient wit

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5

Kattadige, Chamara Manoj Madarasinghe. "Network and Content Intelligence for 360 Degree Video Streaming Optimization." Thesis, The University of Sydney, 2023. https://hdl.handle.net/2123/29904.

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In recent years, 360° videos, a.k.a. spherical frames, became popular among users creating an immersive streaming experience. Along with the advances in smart- phones and Head Mounted Devices (HMD) technology, many content providers have facilitated to host and stream 360° videos in both on-demand and live stream- ing modes. Therefore, many different applications have already arisen leveraging these immersive videos, especially to give viewers an impression of presence in a digital environment. For example, with 360° videos, now it is possible to connect people in a remote meeting in an

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6

Abernot, Madeleine. "Digital oscillatory neural network implementation on FPGA for edge artificial intelligence applications and learning." Electronic Thesis or Diss., Université de Montpellier (2022-....), 2023. http://www.theses.fr/2023UMONS074.

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Au cours des dernières décennies, la multiplication des objets embarqués dans de nombreux domaines a considérablement augmenté la quantité de données à traiter et la complexité des tâches à résoudre, motivant l'émergence d'algorithmes probabilistes d'apprentissage tels que l'intelligence artificielle (IA) et les réseaux de neurones artificiels (ANN). Cependant, les systèmes matériels pour le calcul embarqué basés sur l'architecture von Neuman ne sont pas efficace pour traiter cette quantité de données. C'est pourquoi des paradigmes neuromorphiques dotés d'une mémoire distribuée sont étudiés, s

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7

Ben, ameur Ayoub. "Artificial intelligence for resource allocation in multi-tenant edge computing." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAS019.

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Dans cette thèse, nous considérons le Edge Computing (EC) comme un environnement multi-tenant où les Opérateurs Réseau (NOs) possèdent des ressources en périphérie déployées dans les stations de base, les bureaux centraux et/ou les boîtiers intelligents, les virtualisent, et permettent aux Fournisseurs de Services tiers (SPs) - ou tenants - de distribuer une partie de leurs applications en périphérie afin de répondre aux demandes des utilisateurs. Les SPs aux besoins hétérogènes coexistent en périphérie, allant des Communications Ultra-Fiables à Latence Ultra-Basse (URLLC) pour le contrôle des

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8

Laroui, Mohammed. "Distributed edge computing for enhanced IoT devices and new generation network efficiency." Electronic Thesis or Diss., Université Paris Cité, 2022. http://www.theses.fr/2022UNIP7078.

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Dans le cloud computing, les services et les ressources sont centralisés dans des centres de données auxquels l’utilisateur peut accéder à partir de ses appareils connectés. L’infrastructure cloud traditionnelle sera confrontée à une série de défis en raison de la centralisation de calcul, du stockage et de la mise en réseau dans un petit nombre de centres de données, et de la longue distance entre les appareils connectés et les centres de données distants. Pour répondre à ce besoin, l’edge computing s’appuie sur un modèle dans lequel les ressources de calcul sont distribuées dans le edge de r

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9

Minerva, Roberto. "Will the Telco survive to an ever changing world ? Technical considerations leading to disruptive scenarios." Thesis, Evry, Institut national des télécommunications, 2013. http://www.theses.fr/2013TELE0011/document.

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Le secteur des télécommunications passe par une phase délicate en raison de profondes mutations technologiques, principalement motivées par le développement de l'Internet. Elles ont un impact majeur sur l'industrie des télécommunications dans son ensemble et, par conséquent, sur les futurs déploiements des nouveaux réseaux, plateformes et services. L'évolution de l'Internet a un impact particulièrement fort sur les opérateurs des télécommunications (Telcos). En fait, l'industrie des télécommunications est à la veille de changements majeurs en raison de nombreux facteurs, comme par exemple la b

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10

PELUSO, VALENTINO. "Optimization Tools for ConvNets on the Edge." Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2845792.

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11

Foroughi, Parisa. "Towards network automation : planning and monitoring." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT038.

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La gestion de réseau subit des changements radicaux en raison des attentes élevées de l’infrastructure pour supporter de nouveaux services. Les diverses exigences de ces services nécessitent l’intégration de nouvelles technologies habilitantes qui compliquent le processus de surveillance et de planification du réseau. Par conséquent, pour alléger la charge et augmenter la précision de la surveillance et de la planification, des solutions plus automatisées au niveau des éléments/dispositifs sont nécessaires. Dans cette thèse, nous proposons un cadre semi-automatique appelé AI-driven telemetry (

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12

Busacca, Fabio Antonino. "AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge." Doctoral thesis, Università degli Studi di Palermo, 2022. https://hdl.handle.net/10447/573371.

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5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a

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13

Minerva, Roberto. "Will the Telco survive to an ever changing world ? Technical considerations leading to disruptive scenarios." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2013. http://www.theses.fr/2013TELE0011.

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Le secteur des télécommunications passe par une phase délicate en raison de profondes mutations technologiques, principalement motivées par le développement de l'Internet. Elles ont un impact majeur sur l'industrie des télécommunications dans son ensemble et, par conséquent, sur les futurs déploiements des nouveaux réseaux, plateformes et services. L'évolution de l'Internet a un impact particulièrement fort sur les opérateurs des télécommunications (Telcos). En fait, l'industrie des télécommunications est à la veille de changements majeurs en raison de nombreux facteurs, comme par exemple la b

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14

Lanzarone, Lorenzo Biagio. "Manutenzione predittiva di macchinari industriali tramite tecniche di intelligenza artificiale: una valutazione sperimentale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22853/.

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Nella società è in corso un processo di evoluzione tecnologica, il quale sviluppa una connessione tra l’ambiente fisico e l’ambiente digitale, per scambiare dati e informazioni. Nella presente tesi si approfondisce, nel contesto dell’Industria 4.0, la tematica della manutenzione predittiva di macchinari industriali tramite tecniche di intelligenza artificiale, per prevedere in anticipo il verificarsi di un imminente guasto, identificandolo prima ancora che si possa verificare. La presente tesi è divisa in due parti complementari, nella prima parte si approfondiscono gli aspetti teorici relativ

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15

MINERVA, Roberto. "Will the Telco survive to an ever changing world ? Technical considerations leading to disruptive scenarios." Phd thesis, Institut National des Télécommunications, 2013. http://tel.archives-ouvertes.fr/tel-00917966.

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The telecommunications industry is going through a difficult phase because of profound technological changes, mainly originated by the development of the Internet. They have a major impact on the telecommunications industry as a whole and, consequently, the future deployment of new networks, platforms and services. The evolution of the Internet has a particularly strong impact on telecommunications operators (Telcos). In fact, the telecommunications industry is on the verge of major changes due to many factors, such as the gradual commoditization of connectivity, the dominance of web services

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16

Cherdo, Yann. "Détection d'anomalie non supervisée sur les séries temporelle à faible coût énergétique utilisant les SNNs." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4018.

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Dans le cadre de la maintenance prédictive du constructeur automobile Renault, cette thèse vise à fournir des solutions à faible coût énergétique pour la détection non supervisée d'anomalies sur des séries temporelles. Avec l'évolution récente de l'automobile, de plus en plus de données sont produites et doivent être traitées par des algorithmes d'apprentissage automatique. Ce traitement peut être effectué dans le cloud ou directement à bord de la voiture. Dans un tel cas, la bande passante du réseau, les coûts des services cloud, la gestion de la confidentialité des données et la perte de don

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17

Barreto, Ricardo Manuel Carriço. "IoT Edge Computing Neural Networks on Reconfigurable Logic." Master's thesis, 2019. http://hdl.handle.net/10316/87970.

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Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia<br>Nos últimos anos, temos visto a expanção da inteligência artificial em diferentes áreas e dispositivos. No entanto, no ecossistema IoT, temos uma tendência constante a usar a computação na nuvem para armazenar e processar as vastas quantidades de dados geradas por estes dispositivos, devido aos recursos locais limitados. Esta dissertação propõe a implementa çãao de dispositivos IoT inteligentes capazes de fornecer informações específicas a partir de dados produz

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18

Wong, Jun Hua. "Efficient Edge Intelligence in the Era of Big Data." Thesis, 2021. http://hdl.handle.net/1805/26385.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Smart wearables, known as emerging paradigms for vital big data capturing, have been attracting intensive attentions. However, one crucial problem is their power-hungriness, i.e., the continuous data streaming consumes energy dramatically and requires devices to be frequently charged. Targeting this obstacle, we propose to investigate the biodynamic patterns in the data and design a data-driven approach for intelligent data compression. We leverage Deep Learning (DL), more specifically, Convolutional Autoencoder (CAE), to learn a spa

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19

Gupta, Rachana Ashok. "An edge-detection and HPF based intelligent space a network based integrated navigation system /." 2006. http://www.lib.ncsu.edu/theses/available/etd-05072006-132525/unrestricted/etd.pdf.

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20

(11013474), Jun Hua Wong. "Efficient Edge Intelligence In the Era of Big Data." Thesis, 2021.

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Smart wearables, known as emerging paradigms for vital big data capturing, have been attracting intensive attentions. However, one crucial problem is their power-hungriness, i.e., the continuous data streaming consumes energy dramatically and requires devices to be frequently charged. Targeting this obstacle, we propose to investigate the biodynamic patterns in the data and design a data-driven approach for intelligent data compression. We leverage Deep Learning (DL), more specifically, Convolutional Autoencoder (CAE), to learn a sparse representation of the vital big data. The minimized energ

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21

(10716561), Sanket Ramesh Joshi. "HBONEXT: AN EFFICIENT DNN FOR LIGHT EDGE EMBEDDED DEVICES." Thesis, 2021.

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<div>Every year the most effective Deep learning models, CNN architectures are showcased based on their compatibility and performance on the embedded edge hardware, especially for applications like image classification. These deep learning models necessitate a significant amount of computation and memory, so they can only be used on high-performance computing systems like CPUs or GPUs. However, they often struggle to fulfill portable specifications due to resource, energy, and real-time constraints. Hardware accelerators have recently been designed to provide the computational resources that A

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22

"Study of Knowledge Transfer Techniques For Deep Learning on Edge Devices." Master's thesis, 2018. http://hdl.handle.net/2286/R.I.49325.

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abstract: With the emergence of edge computing paradigm, many applications such as image recognition and augmented reality require to perform machine learning (ML) and artificial intelligence (AI) tasks on edge devices. Most AI and ML models are large and computational heavy, whereas edge devices are usually equipped with limited computational and storage resources. Such models can be compressed and reduced in order to be placed on edge devices, but they may loose their capability and may not generalize and perform well compared to large models. Recent works used knowledge transfer techniques

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23

(10911822), Priyank Kalgaonkar. "AI on the Edge with CondenseNeXt: An Efficient Deep Neural Network for Devices with Constrained Computational Resources." Thesis, 2021.

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Research work presented within this thesis propose a neoteric variant of deep convolutional neural network architecture, CondenseNeXt, designed specifically for ARM-based embedded computing platforms with constrained computational resources. CondenseNeXt is an improved version of CondenseNet, the baseline architecture whose roots can be traced back to ResNet. CondeseNeXt replaces group convolutions in CondenseNet with depthwise separable convolutions and introduces group-wise pruning, a model compression technique, to prune (remove) redundant and insignificant elements that either are irreleva

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24

Kalgaonkar, Priyank B. "AI on the Edge with CondenseNeXt: An Efficient Deep Neural Network for Devices with Constrained Computational Resources." Thesis, 2021. http://dx.doi.org/10.7912/C2/64.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Research work presented within this thesis propose a neoteric variant of deep convolutional neural network architecture, CondenseNeXt, designed specifically for ARM-based embedded computing platforms with constrained computational resources. CondenseNeXt is an improved version of CondenseNet, the baseline architecture whose roots can be traced back to ResNet. CondeseNeXt replaces group convolutions in CondenseNet with depthwise separable convolutions and introduces group-wise pruning, a model compression technique, to prune (remove)

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25

Ganin, Iaroslav. "Natural image processing and synthesis using deep learning." Thèse, 2019. http://hdl.handle.net/1866/23437.

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Nous étudions dans cette thèse comment les réseaux de neurones profonds peuvent être utilisés dans différents domaines de la vision artificielle. La vision artificielle est un domaine interdisciplinaire qui traite de la compréhension d’images et de vidéos numériques. Les problèmes de ce domaine ont traditionnellement été adressés avec des méthodes ad-hoc nécessitant beaucoup de réglages manuels. En effet, ces systèmes de vision artificiels comprenaient jusqu’à récemment une série de modules optimisés indépendamment. Cette approche est très raisonnable dans la mesure où, avec peu de données, el

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