Log in

Relevant bibliographies by topics / Cloud-Based Machine Learning / Dissertations / Theses

To see the other types of publications on this topic, follow the link: Cloud-Based Machine Learning.

Dissertations / Theses on the topic 'Cloud-Based Machine Learning'

Author: Grafiati

Published: 7 June 2025

Last updated: 17 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 21 dissertations / theses for your research on the topic 'Cloud-Based Machine Learning.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

1

You, Yantian. "Cloud Auto-Scaling Control Engine Based on Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239066.

Full text

Abstract:

With the development of modern data centers and networks, many service providers have moved most of their computing functions to the cloud. Considering the limitation of network bandwidth and hardware or virtual resources, how to manage different virtual resources in a cloud environment so as to achieve better resource allocation is a big problem. Although some cloud infrastructures provide simple default auto-scaling and orchestration mechanisms, such as OpenStack Heat service, they usually only depend on a single parameter, such as CPU utilization and cannot respond to the network changes

APA, Harvard, Vancouver, ISO, and other styles

2

Zheng, Yao. "Privacy Preservation for Cloud-Based Data Sharing and Data Analytics." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73796.

Full text

Abstract:

Data privacy is a globally recognized human right for individuals to control the access to their personal information, and bar the negative consequences from the use of this information. As communication technologies progress, the means to protect data privacy must also evolve to address new challenges come into view. Our research goal in this dissertation is to develop privacy protection frameworks and techniques suitable for the emerging cloud-based data services, in particular privacy-preserving algorithms and protocols for the cloud-based data sharing and data analytics services. Cloud co

APA, Harvard, Vancouver, ISO, and other styles

3

Lindeman, Victor. "An Analysis of Cloud-Based Machine Learning Models for Traffic-Sign Classification." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160022.

Full text

Abstract:

The machine learning method deep neural networks are commonly used for artificial intelligence applications such as speech recognition, robotics, and computer vision. Deep neural networks often have very good accuracy, the downside is the complexity of the computations. To be able to use deep neural network models on devices with less computing power, such as smart-phones e.g., can the model run on the cloud and send the results to the device. This thesis will evaluate the possibility to use a smart-phone as a camera unit with Googles open source neural network called Inception, to identify t

APA, Harvard, Vancouver, ISO, and other styles

4

Olsson, Fredrik. "Feature Based Learning for Point Cloud Labeling and Grasp Point Detection." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150785.

Full text

Abstract:

Robotic bin picking is the problem of emptying a bin of randomly distributedobjects through a robotic interface. This thesis examines an SVM approach to ex-tract grasping points for a vacuum-type gripper. The SVM is trained on syntheticdata and used to classify the points of a non-synthetic 3D-scanned point cloud aseither graspable or non-graspable. The classified points are then clustered intograspable regions from which the grasping points are extracted. The SVM models and the algorithm as a whole are trained and evaluated againstcubic and cylindrical objects. Separate SVM models are trained

APA, Harvard, Vancouver, ISO, and other styles

5

Nordlund, Fredrik Hans. "Enabling Network-Aware Cloud Networked Robots with Robot Operating System : A machine learning-based approach." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-160877.

Full text

Abstract:

During the recent years, a new area called Cloud Networked Robotics (CNR) has evolved from conventional robotics, thanks to the increasing availability of cheap robot systems and steady improvements in the area of cloud computing. Cloud networked robots refers to robots with the ability to offload computation heavy modules to a cloud, in order to make use of storage, scalable computation power, and other functionalities enabled by a cloud such as shared knowledge between robots on a global level. However, these cloud robots face a problem with reachability and QoS of crucial modules that are o

APA, Harvard, Vancouver, ISO, and other styles

6

Minelli, Michele. "Fully homomorphic encryption for machine learning." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE056/document.

Full text

Abstract:

Le chiffrement totalement homomorphe permet d’effectuer des calculs sur des données chiffrées sans fuite d’information sur celles-ci. Pour résumer, un utilisateur peut chiffrer des données, tandis qu’un serveur, qui n’a pas accès à la clé de déchiffrement, peut appliquer à l’aveugle un algorithme sur ces entrées. Le résultat final est lui aussi chiffré, et il ne peut être lu que par l’utilisateur qui possède la clé secrète. Dans cette thèse, nous présentons des nouvelles techniques et constructions pour le chiffrement totalement homomorphe qui sont motivées par des applications en apprentissag

APA, Harvard, Vancouver, ISO, and other styles

7

Wiren, Jakob. "Data Storage Cost Optimization Based on Electricity Price Forecasting with Machine Learning in a Multi-Geographical Cloud Environment." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152250.

Full text

Abstract:

As increased demand of cloud computing leads to increased electricity costs for cloud providers, there is an incentive to investigate in new methods to lower electricity costs in data centers. Electricity price markets suffer from sudden price spikes as well as irregularities between different geographical electricity markets. This thesis investigates in whether it is possible to leverage these volatilities and irregularities between different electricity price markets, to offload or move storage in order to reduce electricity price costs for data storage. By forecasting four different electri

APA, Harvard, Vancouver, ISO, and other styles

8

Mohammed, Bashir. "A Framework for Efficient Management of Fault Tolerance in Cloud Data Centres and High-Performance Computing Systems: An Investigation and Performance analysis of a Cloud Based Virtual Machine Success and Failure Rate in a typical Cloud Computing Environment and Prediction Methods." Thesis, University of Bradford, 2019. http://hdl.handle.net/10454/17400.

Full text

Abstract:

Cloud computing is increasingly attracting huge attention both in academic research and industry initiatives and has been widely used to solve advanced computation problem. As cloud datacentres continue to grow in scale and complexity, the risk of failure of Virtual Machines (VM) and hosts running several jobs and processing large amount of user request increases and consequently becomes even more difficult to predict potential failures within a datacentre. However, even though fault tolerance continues to be an issue of growing concern in cloud and HPC systems, mitigating the impact of failur

APA, Harvard, Vancouver, ISO, and other styles

9

Goutierre, Emmanuel. "Machine learning-based particle accelerator modeling." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG106.

Full text

Abstract:

Les accélérateurs de particules reposent sur des simulations de haute précision pour optimiser la dynamique du faisceau. Ces simulations sont coûteuses en ressources de calcul, rendant leur analyse en temps réel difficilement réalisable. Cette thèse propose de surmonter cette limitation en explorant le potentiel de l'apprentissage automatique pour développer des modèles de substitution des simulations d'accélérateurs de particules. Ce travail se concentre sur ThomX, une source Compton compacte, et introduit deux modèles de substitution : LinacNet et Implicit Neural ODE (INODE). Ces modèles son

APA, Harvard, Vancouver, ISO, and other styles

10

Bellafqira, Reda. "Chiffrement homomorphe et recherche par le contenu sécurisé de données externalisées et mutualisées : Application à l'imagerie médicale et l'aide au diagnostic." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0063.

Full text

Abstract:

La mutualisation et l'externalisation de données concernent de nombreux domaines y compris celui de la santé. Au-delà de la réduction des coûts de maintenance, l'intérêt est d'améliorer la prise en charge des patients par le déploiement d'outils d'aide au diagnostic fondés sur la réutilisation des données. Dans un tel environnement, la sécurité des données (confidentialité, intégrité et traçabilité) est un enjeu majeur. C'est dans ce contexte que s'inscrivent ces travaux de thèse. Ils concernent en particulier la sécurisation des techniques de recherche d'images par le contenu (CBIR) et de « m

APA, Harvard, Vancouver, ISO, and other styles

11

Chaudhari, Vijay. "Trust-Based access control in Cloud Computing using machine learning." Thesis, 2018. http://ethesis.nitrkl.ac.in/9878/1/2018_MT_216CS3173_VChaudhari_Trust.pdf.

Full text

Abstract:

Cloud computing is a distributed environment, who hosts very dedicated computing resources accessed anytime from anywhere. This brings many advantages such as flexibility of data access, data omnipresence, and elasticity. As there is no control of data owner over the data so, this brings security threats. In order to securing the cloud environment from the malicious user is a complex task. Over the time various control access model shave been proposed for secure access in the cloud environment such as cryptographic-based access model, identity-based access control model and trust-based access

APA, Harvard, Vancouver, ISO, and other styles

12

Almeida, Gonçalo Vagos Morais Callé de. "Upgrading decision support systems with Cloud-based environments and machine learning." Master's thesis, 2020. http://hdl.handle.net/10362/119345.

Full text

Abstract:

Business Intelligence (BI) is a process for analyzing raw data and displaying it in order to make it easier for business users to take the right decision at the right time. Inthe market we can find several BI platforms. One commonly used BI solution is calledMicroStrategy, which allows users to build and display reports.Machine Learning (ML) is a process of using algorithms to search for patterns in data which are used to predict and/or classify other data.In recent years, these two fields have been integrated into one another in order to try to complement the prediction side of BI to enable

APA, Harvard, Vancouver, ISO, and other styles

13

Chou, Chia-Chin, and 周佳慶. "A Cloud based Application Classification Service Platform with Machine Learning Algorithms." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/31651697670617571889.

Full text

Abstract:

碩士<br>國立清華大學<br>通訊工程研究所<br>101<br>The thesis is based on the thesis “On the Cloud-Based Network Traffic Classification and Applications Identification Services” proposed by Master Gin-Yuan-Jai in 2012. The thesis proposed by Master Gin-Yuan-Jai in 2012 proposes a machine learning-based high-accuracy algorithm called “APPlication Round method (APPR)” to identify network application traffic at the early stage. For each TCP/UDP flow, discriminators available at the early stage are determined to support high-accuracy traffic classification. But the accuracy for the real-time traffic classification

APA, Harvard, Vancouver, ISO, and other styles

14

Lu, Kuei-Heng, and 呂奎亨. "A High Efficiency Massive Spam Filtering Cloud System Based on Machine Learning." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/18199191220375209863.

Full text

Abstract:

碩士<br>康寧大學<br>數位應用研究所<br>103<br>In the era of big data, the spam mails and their variants could be produced like a stream. Since to the speed of receiving e-mails is faster than the processing capacity of the traditional anti-spam systems, the problem of spam will be more serious. Therefore, improving the performance of filtering and analyzing in anti-spam systems is a big challenge. In this paper we focus on the design and implementation of A High Efficiency Massive Spam Filtering Cloud System Based on Machine Learning. Via the high-performance computing power of the cloud systems, the time o

APA, Harvard, Vancouver, ISO, and other styles

15

CHANG, CHUN-CHENG, and 張君丞. "Using Machine Learning on Social Platform and Chatbot based on Cloud Computing." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/f3wmh3.

Full text

Abstract:

碩士<br>國立虎尾科技大學<br>資訊工程系碩士班<br>107<br>Food safety has always been an issue greatly concerned by people, and a lot of information about food and medicine can be found on the Internet. Nevertheless, the information on the Internet is quite complicated, some of which might even be incorrect. Therefore, the topics to be explored in this paper are how to find out the information of food safety from this massive information and avoid being misadvised by the incorrect information of food safety on the Internet. In this study, the Integrating Machine Learning on Social Platform and Chatbot based on Clo

APA, Harvard, Vancouver, ISO, and other styles

16

Basilakis, Jim. "Cloud-based homomorphic encryption for privacy-preserving machine learning in clinical decision support." Thesis, 2020. http://hdl.handle.net/1959.7/uws:60555.

Full text

Abstract:

While privacy and security concerns dominate public cloud services, Homomorphic Encryption (HE) is seen as an emerging solution that ensures secure processing of sensitive data via untrusted networks in the public cloud or by third-party cloud vendors. It relies on the fact that some encryption algorithms display the property of homomorphism, which allows them to manipulate data meaningfully while still in encrypted form; although there are major stumbling blocks to overcome before the technology is considered mature for production cloud environments. Such a framework would find particular rel

APA, Harvard, Vancouver, ISO, and other styles

17

Cheng, Ping. "Study on a resource-saving cloud based long-term ECG monitoring system using machine learning algorithms." Thesis, 2018. https://dspace.library.uvic.ca//handle/1828/9235.

Full text

Abstract:

Electrocardiogram (ECG) records the electrical impulses from myocardium, reflects the underlying dynamics of the heart and has been widely exploited to detect and identify cardiac arrhythmias. This dissertation examines a resource-saving cloud based long-term ECG (CLT-ECG) monitoring system which consists of an ECG raw data acquisition system, a mobile device and a serve. Three issues that are critically pertaining to the effectiveness and efficiency of the monitoring system are studied: the detection of life-threatening arrhythmias, the discrimination of normal and abnormal heartbeats to faci

APA, Harvard, Vancouver, ISO, and other styles

18

Nwamuo, Onyekachi. "Hypervisor-based cloud anomaly detection using supervised learning techniques." Thesis, 2020. http://hdl.handle.net/1828/11503.

Full text

Abstract:

Although cloud network flows are similar to conventional network flows in many ways, there are some major differences in their statistical characteristics. However, due to the lack of adequate public datasets, the proponents of many existing cloud intrusion detection systems (IDS) have relied on the DARPA dataset which was obtained by simulating a conventional network environment. In the current thesis, we show empirically that the DARPA dataset by failing to meet important statistical characteristics of real-world cloud traffic data centers is inadequate for evaluating cloud IDS. We analyze,

APA, Harvard, Vancouver, ISO, and other styles

19

Adamu, Hussaini, Mohammed Bashir, Ali M. Bukar, Andrea J. Cullen, and Irfan U. Awan. "An approach to failure prediction in a cloud based environment." 2017. http://hdl.handle.net/10454/12361.

Full text

Abstract:

yes<br>Failure in a cloud system is defined as an even that occurs when the delivered service deviates from the correct intended behavior. As the cloud computing systems continue to grow in scale and complexity, there is an urgent need for cloud service providers (CSP) to guarantee a reliable on-demand resource to their customers in the presence of faults thereby fulfilling their service level agreement (SLA). Component failures in cloud systems are very familiar phenomena. However, large cloud service providers’ data centers should be designed to provide a certain level of availability to the

APA, Harvard, Vancouver, ISO, and other styles

20

Guedes, Diogo Alexandre Amaral Conde. "Object identification for autonomous vehicles based on machine learning." Master's thesis, 2021. http://hdl.handle.net/10773/31213.

Full text

Abstract:

Autonomous driving is one of the most actively researched fields in artificial intelligence. The autonomous vehicles are expected to significantly reduce the road accidents and casualties one day when they become sufficiently mature transport option. Currently much effort is focused to prove the concept of autonomous vehicles that is based on a suit of sensors to observe their surroundings. In particular, camera and LiDAR are researched as an efficient combination of sensors for on-line object identification on the road. 2D object identification is an already established field in Comput

APA, Harvard, Vancouver, ISO, and other styles

21

Taati, BABAK. "Generation and Optimization of Local Shape Descriptors for Point Matching in 3-D Surfaces." Thesis, 2009. http://hdl.handle.net/1974/5107.

Full text

Abstract:

We formulate Local Shape Descriptor selection for model-based object recognition in range data as an optimization problem and offer a platform that facilitates a solution. The goal of object recognition is to identify and localize objects of interest in an image. Recognition is often performed in three phases: point matching, where correspondences are established between points on the 3-D surfaces of the models and the range image; hypothesis generation, where rough alignments are found between the image and the visible models; and pose refinement, where the accuracy of the initial alignments

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!