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.
Results
Showing 1 to 20 of 400 for “"Learning Framework"”.
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Towards a unified multi-agent reinforcement learning framework
The field of Multi-Agent Reinforcement Learning (MARL) has rapidly evolved, yet integrating diverse tasks and algorithms into a cohesive system remains a complex challenge. This thesis proposes a unified framework aimed at improving adaptability, scalability, and cooperative dynamics among agents …
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A Machine Learning Framework for Securing Patient Records
… undetected. This thesis proposes a novel machine learning framework using a density-based local outlier detection model, in addition to employing a Human-in-the-Loop Machine Learning (HILML) approach. The density-based outlier detection model enables patterns in EPR data to be extracted to profile …
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A geospatial deep learning framework for scalable hydrographic mapping
… Dataset (NHD) provides the authoritative spatial framework for surface water representation, yet its reliance on manual interpretation and rule-based workflows limits the timeliness and consistency of updates across diverse landscapes. Traditional hydrologic mapping methods based on Digital …
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Deep adaptive anomaly detection using an active learning framework
… the anomaly detection outcome? We employ a Deep Learning and an Active Learning framework to learn features for anomaly detection. In Active Learning, an Oracle (usually a domain expert) labels a small amount of data over a series of training rounds. The deep neural network is trained after each …
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An Online Adaptive Machine Learning Framework for Autonomous Fault Detection
… Vector Machine (AISOSVM).</p> <p>The AISOSVM framework combines the strengths of the AIS and OSVM to create a fault detection system that can effectively identify faults in complex systems while maintaining adaptability. The framework is designed using Model-Based Systems Engineering (MBSE) …
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A privacy preserving online learning framework for medical diagnosis applications
… in building an accurate online diagnosis framework. Most local sites have small data sets, and machine learning models developed locally based on small data sets, do not have knowledge about other data sets and learning models used at other sites. The work in this thesis utilizes the …
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H3DNET: A Deep Learning Framework for Hierarchical 3D Object Classification
Deep learning has received a lot of attention in the fields such as speech recognition and image classification because of the ability to learn multiple levels of features from raw data. However, 3D deep learning is relatively new but in high demand with their great research values. Current …
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Multi-Objective Reinforcement Learning Framework for Unknown Stochastic & Uncertain Environments
… on the problem of uncertainty handling during learning, by agents dealing in stochastic environments by means of Multi Objective Reinforcement Learning (MORL). Most previous investigations into multi objective reinforcement learning have proposed algorithms to deal with the learning performance …
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Neural Network Training and Inversion with a Bregman Learning Framework
… approaches, this work contributes to both the learning problems and the inversion problems of DNNs. In particular, we propose a lifted Bregman learning framework that goes beyond the classical back-propagation approach, and aims to address unresolved and overlooked issues in training and the …
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A machine learning framework for predictive maintenance of wind turbines
… companies have increasingly turned to machine learning to improve wind turbine reliability. Thus, the goal of this thesis is to create a flexible and extensible machine learning framework that enables wind energy experts to define and build models for the predictive maintenance of wind …
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Tracking engagement : a machine learning framework for estimating affective engagement
… during training courses by applying machine learning techniques to video images. This thesis proposes a framework to measure construction workers' engagement during training courses by unobtrusively analyzing engagement through body and pose estimation, codifying who is speaking and …
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Deep learning framework bridges lab and field scale microseismic focal mechanism
… of these field microseismic waveform data. Deep learning has shown increasing potential in signal processing and data mining, where the term deep refers to its numerous tunable parameters, and learning characterizes the optimization of these parameters. Here, a framework is proposed to re-train …
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DL-DI: A Deep Learning Framework for Distributed, Incremental Image Classification
Deep Learning technologies show promise for dramatic advances in fields such as image classification and speech recognition. Deep Learning (DL) is a class of Machine Learning algorithms that involves learning of multiple levels of features from data to build a model. One of the open questions in DL …
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DPLearn: an effective but concise learning framework based on discriminative patterns
… models have shown strong abilities on many learning tasks since they can easily build high-order interactions between different features and also handle both numerical and categorical features as well as high dimensional features. By taking the advantage of both modeling methodologies, a …
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Orion – A Machine Learning Framework for Unsupervised Time Series Anomaly Detection
… New methods to detect anomalies using machine learning are continuously emerging. However, algorithms alone only solve one aspect of the problem – finding anomalies. Existing systems often fail to encompass an end-to-end detection process, to facilitate comparative analysis of various anomaly …
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Deep learning framework for solving geoacoustic inversion problems using normal mode theory
… characterization. This thesis presents a deep learning framework to overcome these limitations in shallow-water environments. The core approach involves training one-dimensional convolutional neural networks (1D-CNN) on large synthetic datasets generated using the KRAKEN normal mode acoustic …
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Automated AI Classification of Midpalatal Suture Maturation Stages Using Deep Learning Framework
… plan appropriately. This study proposes a deep learning framework to classify midpalatal suture maturation stages using CBCT images. 1200 images were collected and oriented in three planes on Dolphin Imaging Software. After removing images with poorly defined sutures, the final sample consisted …
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Towards a Reliable Deep Learning Framework for Prostate Cancer Diagnosis using Ultrasound
… for improving patient outcomes. Developing deep learning (DL) models for PCa detection is hindered by noisy labels and cancer heterogeneity. The purpose of this work is to develop a clinically applicable framework for DL-based detection of PCa from ultrasound that is robust to noise and …
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The Barriers Teachers Face When Implementing the Universal Design for Learning Framework
<p>There are multiple barriers to learning that students face. Universal Design for Learning (UDL) is a framework for teaching and learning that gives all students an equal opportunity to succeed. While many studies address the hurdles teachers face when implementing the UDL framework, there is a …
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