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Cerca per relatore della tesi

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Titolo Corso di studi Anno di discussione Relatore
Design and experimentation of a feature importance measure for distributed and federated setup ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2026
Extracting Region-Aware Counterfactual Rules for Model-Agnostic Explainable Artificial Intelligence COMPUTER ENGINEERING 2025
Development of Deep Learning Systems for Vehicle Damage Detection and Segmentation ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2025
Design and evaluation of an ensemble of latent spaces to generate counterfactuals for explainable multiclass emotion recognition ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2025
Input-diversified ensemble of counterfactual-based feature importances to approximate the explanation of monolithic machine learning model ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2025
Analysis of a counterfactual-based feature importance measure: fidelity, computational cost and influencing factors ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2025
A double quantization approach for autonomous concept learning in sleep staging ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2025
Design and Experimentation of a Novel Feature Importance Measure and Rule-Extraction Approach Based on Non-Minimal Counterfactuals ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2024
Enabling Concept-Embedding Models for Sleep Staging through Automatic Prototype-Based Learning of Concepts ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2024
Development of a power consumption clustering in the manufacturing sector based on data mining techniques COMPUTER ENGINEERING 2024
Design and testing of a weighted aggregation method for a conterfactual-based feature importance measure and its application to industrial production quality recognition COMPUTER ENGINEERING 2024
A parametric counterfactual-based feature importance measure for explainable regression of product quality ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING 2024

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