Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 18 of 18 for “"Machine and deep learning"”.
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Characterising Algorithm Debt in Machine and Deep Learning Systems
The integration of Machine and Deep Learning (ML/DL) into modern software systems has transformed application domains such as finance, healthcare, and autonomous technologies. However, the complexity of ML/DL algorithms, the unique development pipeline, and the stochastic training process introduce …
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Characterising Algorithm Debt in Machine and Deep Learning Systems
The integration of Machine and Deep Learning (ML/DL) into modern software systems has transformed application domains such as finance, healthcare, and autonomous technologies. However, the complexity of ML/DL algorithms, the unique development pipeline, and the stochastic training process introduce …
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Digital Phenotyping and Genomic Prediction Using Machine and Deep Learning in Animals and Plants
This dissertation investigates the utility of deep learning and machine learning approaches for livestock management and quantitative genetic modeling of rice grain size under climate change. Monitoring the live body weight of animals is crucial to support farm management decisions due to its …
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Role of handwriting analysis through machine and deep learning to support the diagnosis of cognitive impairment
Contains fulltext : 299449.pdf (Publisher’s version ) (Open Access)
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Machine and Deep Learning Approach for Type 2 Diabetes Prediction Using the CDC’s BRFSS Dataset: A Retrospective Analysis
… etiology with social, environmental, behavioral, and genetic risk factors. It is associated with serious microvascular and macrovascular complications which are also associated with increased morbidity, mortality, and health expenditure. However, early detection, lifestyle changes and treatment …
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Detection of data leakage and disruption of covert timing channel in secure drone communication using machine and deep learning
… a substantial increase in both the United States and globally. However, it is noteworthy that most drones, classified as Internet of Things devices, are produced with a limited security lifecycle. This study's findings are of paramount importance, as traditional computing exploits can be applied …
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Batch Query Memory Prediction Using Deep Query Template Representations
… LearnedWMP for predicting the memory cost demand of a batch of queries in a database workload. Existing techniques focus on estimating the resource demand of individual queries, failing to capture the net resource demand of a workload. LearnedWMP leverages the query plan and groups queries …
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EnogisAI: An Artificial Intelligence Framework for Predictive Agronomics
Ensuring the quality and health standards necessary to feed the growing population is a critical challenge. Smart farming technologies combined with artificial intelligence (AI) represent an opportunity to improve crop quality and yield while efficiently and sustainably using the available …
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The Search for Dark Photons at LHCb and Machine Learning in Particle Physics
… world-leading limits in searches for prompt-like and long-lived dark photons decaying into two muons, as well as other dimuon resonances, produced in proton-proton collisions and collected by the LHCb experiment at the Large Hadron Collider at CERN. In addition, this thesis proposes various …
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Evaluation and Development of Liquefaction Occurrence and Consequence Analytics Driven by Emerging Data and Technologies
… that require only geologic or geospatial data, and which are accessible to a broad userbase; or (ii) semi-mechanistic “simplified stress-based” models that are based on in-situ tests, and which are generally limited to use by geoengineers, with cone-penetration-test (CPT) based models currently …
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Valuazione automatica della complessità di frasi in Italiano e Inglese tramite Deep Learning.
… the improvement of the personal capital, and the personal independence. Although the importance of literacy skills, the current panorama of linguistic proficiency is wide, and it extends from highly literates to people who have difficulties understanding daily-life texts. Society …
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A framework for proactive fault tolerance in cloud-IoT applications
… the cloud has several benefits, including expanding local IoT resources and improving cloud-IoT application performance. Cloud computing can benefit from IoT devices and applications by extending its scope to include real-world surroundings. On the other hand, IoT can use the cloud’s unlimited …
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DeepGeoMap
In recent years, deep learning improved the way remote sensing data is processed. The classification of hyperspectral data is no exception. 2D or 3D convolutional neural networks have outperformed classical algorithms on hyperspectral image classification in many cases. However, geological …
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Applications of Machine Learning to the Petrographic Analysis of Icelandic Gabbroic Xenoliths through Light, Electron and X-ray Microscopy
… the development of novel methods incorporating machine learning and deeplearning methods for use in petrographic analysis. The first of these chapters introduces adeep learning framework for the detection and segmentation of individual crystals fromoptical microscopy scans of thin sections; in …
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Drivers of landscape evolution in northern ecosystems: Shrub expansion, vegetation-fire interaction, and permafrost degradation
… properties controlling ecosystem carbon and energy dynamics, such as plant community composition and permafrost stability may shift in response to novel climate regimes. In the tundra of northern and northwestern Alaska, some of the most profound terrestrial responses to recent climate …
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Hybrid Words Representation for the classification of low quality text
… others. For instance, we talk, give our opinions and suggestions all using natural language; to be more precise, we use words while communicating with others. However, in today's world, we wish to communicate with computers, just like humans. It is not an easy task because human communicate in an …
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Integrating Machine Learning Into Process-Based Modeling to Predict Ammonia Losses From Stored Liquid Dairy Manure
… its fertilizer value, reducing management costs, and minimizing potential environmental pollution challenges. However, ammonia loss through volatilization during storage remains a challenge. Quantifying these losses is necessary to inform decision-making processes to improve manure management, and …
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A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations
This work presents a novel and modern method for reactor modeling, simulation, and uncertainty characterization through an integrated framework developed under the terminology of combining four fundamental principles in scientific modeling and computing: Physics, Models, Data, and UQ (Uncertainty …