6 papers
Alternating Bi-Objective Optimization for Explainable Neuro-Fuzzy Systems
Qusai Khaled, Uzay Kaymak, Laura Genga
Fuzzy systems show strong potential in explainable AI due to their rule-based architecture and linguistic variables. Existing approaches navigate the accuracy-explainability trade-…
Predictive Maintenance for Ultrafiltration Membranes Using Explainable Similarity-Based Prognostics
Qusai Khaled, Laura Genga, Uzay Kaymak
In reverse osmosis desalination, ultrafiltration (UF) membranes degrade due to fouling, leading to performance loss and costly downtime. Most plants rely on scheduled preventive ma…
Explainable Uncertainty Quantification for Wastewater Treatment Energy Prediction via Interval Type-2 Neuro-Fuzzy System
Qusai Khaled, Bahjat Mallak, Uzay Kaymak +1
Wastewater treatment plants consume 1-3% of global electricity, making accurate energy forecasting critical for operational optimization and sustainability. While machine learning…
Explainable Fuzzy GNNs for Leak Detection in Water Distribution Networks
Qusai Khaled, Pasquale De Marinis, Moez Louati +3
Timely leak detection in water distribution networks is critical for conserving resources and maintaining operational efficiency. Although Graph Neural Networks (GNNs) excel at cap…
DistillFSS: Synthesizing Few-Shot Knowledge into a Lightweight Segmentation Model
Pasquale De Marinis, Pieter M. Blok, Uzay Kaymak +3
Cross-Domain Few-Shot Semantic Segmentation (CD-FSS) seeks to segment unknown classes in unseen domains using only a few annotated examples. This setting is inherently challenging:…
Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design
Pasquale De Marinis, Uzay Kaymak, Rogier Brussee +2
Few-Shot Semantic Segmentation (FSS) models achieve strong performance in segmenting novel classes with minimal labeled examples, yet their decision-making processes remain largely…