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 23 for “"AI Framework"”.
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Generative AI Framework for 3D Object Generation in Augmented Reality
This thesis presents a framework that integrates state-of-the-art generative AI models for real-time creation of three-dimensional (3D) objects in augmented reality (AR) environments. The primary goal is to convert diverse inputs, such as images and speech, into accurate 3D models, enhancing user …
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Explainable AI framework through Multi-Context Multi-Dimensional Graph Neural Network
… to surmount these obstacles. GNNs displayed a flair for harnessing the relational dynamics inherent in complex systems such as social media, focus groups, and literature explaining the symbiosis between sentiment, context, and digital community. These relationships were converted into dense …
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CodeLens: A generative ai framework for dynamic feedback on SQL semantic errors
This Thesis was approved for publication on 2024-12-06 at 16:45.
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Alive Scene: Participatory Multimodal AI Framework for Collective Narratives in Dynamic 3D Scene
… through the Contrastive Language-Image Pretraining (CLIP) model. These methods are currently among the most popular and efficient. The platform continually enriches its collection of users' views and interpretations through interactions with this semantic AI system, enabling the archiving of …
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A Computer Vision and Generative AI Framework for Trend Extraction and Brand-Aligned Fashion Design
… competitive, putting pressure on mass-market retailers to outperform their competitors. This thesis presents a novel framework to help retailers shorten the design-to-market turnaround time. The key concept is to use computer vision and unsupervised clustering techniques to identify trends from …
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Building trust in autonomous systems with an AI framework for privacy, safety, and reliability in data, software, and robotics
In this research, we propose an innovative framework designed to enhance privacy, safety, and reliability in data science, software development, and AI-empowered robotics, with a primary focus on building trust in autonomous systems. Our approach initially emphasizes the application of deep …
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Self-Supervised ECG Learning for Multimodal Clinical Tasks
We present a multimodal clinical AI framework that integrates time series, images, and text to support robust diagnostic reasoning across diverse input combinations. We first introduce ECG-JEPA, a self-supervised encoder pretrained on multiple ECG datasets to learn generalizable time series …
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AI-informed model analogs for subseasonal-to-seasonal prediction
… preparedness, and agriculture, and yet it remains a particularly challenging timescale to predict. We explore the use of an interpretable AI-informed model analog forecasting approach, previously employed on longer timescales, to improve S2S predictions. Using an artificial neural network, we …
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Healthcare Agents: Large Language Models in Health Prediction and Decision-Making
… we explore two critical aspects in healthcare AI: (1) leveraging LLMs for multimodal health prediction from wearable sensor data and (2) developing collaborative AI framework for medical decision-making. We first introduce a Health-LLM framework that performs multimodal fusion of temporal …
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Privacy-Focused LLM for local data processing: Implementing OLLAMA and RAG to securely query personal files in closed environments
… privacy and security associated with cloud-based AI systems by developing a locally hosted, privacy-preserving AI framework. The solution is designed to provide advanced AI functionalities, ensuring organizations retain full control over their sensitive data while maintaining operational …
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Differential Privacy in Reinforcement Learning
Reinforcement learning is a principled AI framework for autonomously experience-driven learning. The primary goal of reinforcement learning is to train autonomous agents to learn the optimal behaviors for their interactive environments. Deep reinforcement learning promotes a higher-level …
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Episodic Detail Production and Semantic Coherence in Down Syndrome and Fragile X Syndrome: Longitudinal Findings from Expressive Language Sampling
… abilities. This study examined episodic detail production and narrative coherence in children and adolescents with Down syndrome (DS) and Fragile X syndrome (FXS) using conversational samples from the Expressive Language Sampling (ELS) Conversation task (Abbeduto et al., 2020, 2023). …
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ESSAYS ON OPTIMIZATION AND SUPPLY CHAIN STRATEGIES FOR SUSTAINABLE SYSTEMS: INSIGHTS FROM FRACTAL DIMENSION IMAGE ANALYSIS, PHOTOVOLTAIC MANUFACTURING RESILIENCE, AND FRESH PRODUCE INFRASTRUCTURE
Sustainable systems engineering increasingly relies on quantitative models that connect methodological advances with real supply-chain decisions in energy and food systems. This dissertation integrates two pillars of systems engineering—optimization and supply-chain analysis—across three essays: …
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Enhancing player experience in computer games: A computational Intelligence approach.
… game artificial intelligence. Research in game AI has traditionally been focused on improving its competency. However, a competent game AI does not directly correlate to the satisfaction and entertainment value experienced by the human player. This thesis focuses on addressing two key issues of …
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Selective prioritisation of real-time IP packets to improve quality of service in 5G wireless sensor networks
… a novel, multi-stage Artificial Intelligence (AI) framework that enables a transition from passive network analysis to active, autonomous control. The central research question investigates whether a hierarchical suite of Machine Learning (ML), Deep Learning (DL), and Deep Reinforcement …
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Narrative Maps: A Computational Model to Support Analysts in Narrative Sensemaking
… a narrative model and visualization method to aid analysts with this process. In particular, we propose the narrative maps framework—an event-based representation that uses a directed acyclic graph to represent the narrative structure—and a series of empirically defined design guidelines for …
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Evolving Video Analysis: From Object Perception to Holistic Understanding
The domain of video content analysis has experienced rapid advancements due to the proliferation of digital video content and the evolving capabilities of computer vision technologies. Despite these advancements, significant challenges remain in both video object perception and holistic video …
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REPURPOSING DEEPFAKES FOR SOCIAL GOOD: THEORY, EMPIRICAL EVIDENCE, AND AI SYSTEMS FOR BIAS MEASUREMENT AND MITIGATION
… used for bias measurement across various domains. These methods have proven highly effective when applied to textual contexts, where researchers can easily manipulate bias-sensitive attributes like race or age while keeping all other content identical to isolate the causal effects of bias. …
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Explainable and Robust Data-Driven Machine Learning Methods for Digital Healthcare Monitoring
… explores projects spanning various healthcare domains. Explainable and robust machine-learning solutions are proposed and tested, which include novel signal processing guidelines, innovative feature engineering methods, and pioneering deep-learning networks. These solutions contribute to the …
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Data Intensive Method For Processing Defect Detection and Mitigation For Composites
… by both techniques. Artificial intelligence (AI) applications in composite manufacturing offer promising solutions for automated quality inspection; however, practical implementation is limited by the lack of in situ imaging data and effective anomaly detection models trained specifically for …
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