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 20 of 47 for “"Explainable artificial intelligence"”.
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Reliability Assessment Methods for Explainable Artificial Intelligence
L'abstract è presente nell'allegato / the abstract is in the attachment
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Explainable artificial intelligence for inclusive automatic speech recognition
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01
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An Explainable Artificial Intelligence Approach Based on Deep Type-2 Fuzzy Logic System
Artificial intelligence (AI) systems have benefitted from the easy availability of computing power and the rapid increase in the quantity and quality of data which has led to the widespread adoption of AI techniques across a wide variety of fields. However, the use of complex (or Black box) AI …
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Explainable artificial intelligence and deep reconstruction of hyperspectral images for advancing sweetpotato quality evaluation
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01
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Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)
… networks has generated a remarkable growth in Artificial Intelligence (AI) research, and it received much interest over the past few years. However, one of the main challenges for the broad adoption of deep learning based models such as Convolutional Neural Networks (CNN) is the lack of …
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Accurate Uncertainty Quantification and Explainable Artificial Intelligence in Machine Learning Models for Toxicological Risk Assessment
Consumer and environmental safety decisions can be supported by Quantitative Structure-Activity Relationship (QSAR) models – a key part of the Next Generation Risk Assessment strategy for animal-free safety. Machine learning methods are often employed to build QSAR models, but these “black box” …
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The Role of Explainable Artificial Intelligence in Data Science [Il Ruolo dell'Intelligenza Artificiale Esplicabile nella Scienza dei Dati]
… in particolare quelli basati su Intelligenza Artificiale (IA) e apprendimento automatico (ML), come imperativi strategici. La crescente complessità degli algoritmi di apprendimento automatico accelera la domanda parallela di modelli trasparenti e interpretabili. La tesi inizia con …
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The Use Of Multiple Saliency Techniques As an Explanation Interface In General Image Recognition
… machines that preform beyond that of human intelligence have yet to be implemented into society at large in substantiative ways. Examples in research of AI that can diagnose cancer, narcolepsy, renal diseases, and cardiac damage abound, yet these machines have to be implemented into clinical …
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Advancing Pattern Detection, Theory Development and Decision Making with Explainable AI
The application of explainable artificial intelligence (XAI) methods in data-driven decision-making and computationally intensive theory development (CTD) is a subject of ongoing debate, particularly concerning how and whether these methods can be effectively employed, and how the reliability of …
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Explainable AI: A Unified Approach Based on Cooperative Game Theory
Explainable Artificial Intelligence (XAI) aims to enhance the interpretability of machine learning (ML) models, yet existing feature-based explanation methods remain fragmented across local and global approaches. This thesis presents a unified framework based on cooperative game theory to …
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ARTIFICIAL INTELLIGENCE (AI) APPROACHES IN DRUG DISCOVERY: DEVELOPMENT AND VALIDATION OF NEW STRATEGIES IN VIRTUAL SCREENING CAMPAIGNS
… is increasingly benefitting from the advent of artificial intelligence (AI), which has proven to enhance both the efficiency and accuracy of Computer-Aided Drug Design (CADD), while significantly reducing the associated costs and timelines. This Work examines various case studies in which AI has …
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Investigating the atmospheric and oceanic drivers of Atlantic Multidecadal Variability and predictability
… atmospheric and oceanic predictors. I apply explainable artificial intelligence techniques to highlight a significant source of multidecadal predictability over the Transition Zone in oceanic predictors such as sea surface salinity (SSS) and sea surface height in the presence of external …
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Investigating the Atmospheric and Oceanic Drivers of Atlantic Multidecadal Variability and Predictability
… atmospheric and oceanic predictors. I apply explainable artificial intelligence techniques to highlight a significant source of multidecadal predictability over the Transition Zone in oceanic predictors such as sea surface salinity (SSS) and sea surface height in the presence of external …
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Analysis of bankruptcy prediction of shipping industry - Machine Learning Approach
… across 1, 3, and 5-year horizons, with Explainable Artificial Intelligence (XAI) techniques employed to interpret the impact of each variable. The findings reveal that non-financial and macroeconomic variables, such as LIBOR interest rates and trade volume growth rates, are significant …
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Accelerating data-driven discovery in type 1 diabetes: an informatics-based approach
… research. Using approaches firmly rooted in explainable artificial intelligence, we successfully demonstrate the following: (1) development of a computational phenotyping methodology that enables automated diabetes/T1D case identification in heterogeneous, nationwide electronic health record …
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Reliable, secure and energy-efficient AI hardware
… We exploit emerging computing paradigms such as explainable artificial intelligence, neural architecture search, and moving target defense to guarantee reliability, security, and energy efficiency. My Ph.D. thesis is the first effort toward developing energy, reliability, and robustness-aware AI …
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Knowledge-aware Methods for Explainable Decision Support in Lifelong Learning
… creates significant opportunities for artificial intelligence (AI) to support lifelong learning. To make such intelligent support effective in real-world educational settings, careful planning, representation, reasoning are essential. This thesis addresses the design, implementation, …
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A generic optimisation framework for reinforcement learning in the foreign exchange market
… utilised in an iterative process during which explainable artificial intelligence techniques are employed to facilitate data-driven state-space optimisation and agent transparency enhancement. The framework culminates in a robust evaluation methodology—comprising multi-seed training, …
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