An Effective Preprocessing Scheme for DoA Estimation in Hybrid Antenna Arrays. - Maria Trigka; Christos Mavrokefalidis; Kostas Berberidis (ICT, 2018)

Trajectory Clustering and k-NN for Robust Privacy Preserving Spatiotemporal Databases. - Elias Dritsas; Maria Trigka; Panagiotis Gerolymatos; Spyros Sioutas (Algorithms, 2018)

Storage Efficient Trajectory Clustering and k-NN for Robust Privacy Preserving Spatio-Temporal Databases. - Elias Dritsas; Andreas Kanavos; Maria Trigka; Spyros Sioutas; Athanasios K. Tsakalidis (Algorithms, 2019)

Trajectory Clustering and k-NN for Robust Privacy Preserving k-NN Query Processing in GeoSpark. - Elias Dritsas; Andreas Kanavos; Maria Trigka; Gerasimos Vonitsanos; Spyros Sioutas; Athanasios K. Tsakalidis (Algorithms, 2020)

Full snapshot reconstruction in hybrid architecture antenna arrays. - Maria Trigka; Christos Mavrokefalidis; Kostas Berberidis (EURASIP J. Wirel. Commun. Netw., 2020)

A Distributed Sparse Channel Estimation Technique for mm Wave Massive MIMO Systems. - Maria Trigka; Christos Mavrokefalidis; Kostas Berberidis (EUSIPCO, 2021)

Community Detection Algorithms for Cultural and Natural Heritage Data in Social Networks. - Andreas Kanavos; Maria Trigka; Elias Dritsas; Gerasimos Vonitsanos; Phivos Mylonas (AIAI (Workshops), 2021)

Aspect-Based Community Detection of Cultural Heritage Streaming Data. - Elias Dritsas; Maria Trigka; Gerasimos Vonitsanos; Andreas Kanavos; Phivos Mylonas (IISA, 2021)

A Hierarchical Ontology for Dialogue Acts in Psychiatric Interviews. - Aristeidis Bifis; Maria Trigka; Sofia Dedegkika; Panagiota Goula; Constantinos Constantinopoulos; Dimitrios I. Kosmopoulos (PETRA, 2021)

A Distributed Sparse Channel Estimation Technique for mmWave Massive MIMO Systems. - Maria Trigka; Christos Mavrokefalidis; Kostas Berberidis (CoRR, 2021)

Joint Power and Contrast Shrinking in RGB Images with Exponential Smoothing. - Maria Trigka; Elias Dritsas; Konstantinos Moustakas (IVMSP, 2022)

A Survey on Signal Processing Methods for EEG-based Brain Computer Interface Systems. - Maria Trigka; Elias Dritsas; Christos Fidas (PCI, 2022)

Museum Guidance in Sign Language: the SignGuide project. - Dimitrios I. Kosmopoulos; Constantinos Constantinopoulos; Maria Trigka; Dimitrios Papazachariou; Klimis Antzakas; Venetta Lampropoulou; Antonis A. Argyros; Iason Oikonomidis; Anastasios Roussos; Nikolaos Partarakis; George Papagiannakis; Konstandinos Grigoriadis; et al. (PETRA, 2022)

A Multi-class Classification Approach for Weather Forecasting with Machine Learning Techniques. - Elias Dritsas; Maria Trigka; Phivos Mylonas (SMAP, 2022)

An Apache Spark Implementation for Text Document Clustering. - Elias Dritsas; Maria Trigka; Gerasimos Vonitsanos; Andreas Kanavos; Phivos Mylonas (SMAP, 2022)

Efficient Distributed Multi-Task Schemes for mmWave MIMO Channel Estimation. - Maria Trigka; Christos Mavrokefalidis; Kostas Berberidis (IEEE Access, 2022)

Machine Learning Techniques for Chronic Kidney Disease Risk Prediction. - Elias Dritsas; Maria Trigka (Big Data Cogn. Comput., 2022)

Lung Cancer Risk Prediction with Machine Learning Models. - Elias Dritsas; Maria Trigka (Big Data Cogn. Comput., 2022)

The Predictive Power of a Twitter User's Profile on Cryptocurrency Popularity. - Maria Trigka; Andreas Kanavos; Elias Dritsas; Gerasimos Vonitsanos; Phivos Mylonas (Big Data Cogn. Comput., 2022)

Non-Linear Observer Design with Laguerre Polynomials. - Maria Trigka; Elias Dritsas (Entropy, 2022)

A Methodology for Extracting Power-Efficient and Contrast Enhanced RGB Images. - Elias Dritsas; Maria Trigka (Sensors, 2022)

Stroke Risk Prediction with Machine Learning Techniques. - Elias Dritsas; Maria Trigka (Sensors, 2022)

Data-Driven Machine-Learning Methods for Diabetes Risk Prediction. - Elias Dritsas; Maria Trigka (Sensors, 2022)

Machine Learning Methods for Hypercholesterolemia Long-Term Risk Prediction. - Elias Dritsas; Maria Trigka (Sensors, 2022)

Context-Aware Automatic Sign Language Video Transcription in Psychiatric Interviews. - Erion-Vasilis M. Pikoulis; Aristeidis Bifis; Maria Trigka; Constantinos Constantinopoulos; Dimitrios I. Kosmopoulos (Sensors, 2022)

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks. - Maria Trigka; Elias Dritsas (Sensors, 2022)

Advanced signal processing techniques for next generation mobile networks in the mmWave spectrum (Προχωρημένες τεχνικές επεξεργασίας σήματος για κινητά δίκτυα επόμενης γενιάς στο χιλιοστομετρικό φάσμα συχνοτήτων) - Maria Trigka (2022)

Machine Learning Models for Prostate Cancer Identification. - Elias Dritsas; Maria Trigka; Phivos Mylonas (KDIR, 2023)

Ensemble Machine Learning Models for Breast Cancer Identification. - Elias Dritsas; Maria Trigka; Phivos Mylonas (AIAI (Workshops), 2023)

Influences of Cognitive Styles on EEG-Based Activity: An Empirical Study on Visual Content Comprehension. - Maria Trigka; Georgios Papadoulis; Elias Dritsas; Christos Fidas (INTERACT (4), 2023)

Mental Confusion Prediction in E-Learning Contexts with EEG and Machine Learning. - Maria Trigka; Elias Dritsas; Phivos Mylonas (NiDS (1), 2023)

A Multi-Class Classification Approach for Anemia Level Prediction with Machine Learning Models. - Maria Trigka; Elias Dritsas; Phivos Mylonas (SEEDA-CECNSM, 2023)

An EEG-Based Application for Real-Time Mental State Recognition in Adaptive E-Learning Environment. - Amalia Chrysanthakopoulou; Elias Dritsas; Maria Trigka; Phivos Mylonas (SMAP, 2023)

Supervised Machine Learning Models to Identify Early-Stage Symptoms of SARS-CoV-2. - Elias Dritsas; Maria Trigka (Sensors, 2023)

Supervised Machine Learning Models for Liver Disease Risk Prediction. - Elias Dritsas; Maria Trigka (Comput., 2023)

Efficient Data-Driven Machine Learning Models for Water Quality Prediction. - Elias Dritsas; Maria Trigka (Comput., 2023)

Efficient Data-Driven Machine Learning Models for Cardiovascular Diseases Risk Prediction. - Elias Dritsas; Maria Trigka (Sensors, 2023)

Long-Term Coronary Artery Disease Risk Prediction with Machine Learning Models. - Maria Trigka; Elias Dritsas (Sensors, 2023)

Predicting the Occurrence of Metabolic Syndrome Using Machine Learning Models. - Maria Trigka; Elias Dritsas (Comput., 2023)

An Innovative Multi-Scale Strategy-Based Decision Engine for Zero-Touch Management and Orchestration in 6G. - Golshan Famitafreshi; Maria Trigka; Dimitris Selis; John S. Vardakas; Christos V. Verikoukis (CAMAD, 2024)

New Perspectives in e-Learning: EEG-Based Modelling of Human Cognition Individual Differences. - Maria Trigka; Elias Dritsas; Phivos Mylonas (AIAI (Workshops), 2024)

A Survey on Privacy-Enhancing Techniques in the Era of Artificial Intelligence. - Elias Dritsas; Maria Trigka; Phivos Mylonas (NiDS, 2024)

Eye State Classification Using Ensemble Machine Learning Models and SMOTE on EEG Data. - Maria Trigka; Elias Dritsas; Phivos Mylonas (SEEDA-CECNSM, 2024)

Driver Sleepiness Detection Using Machine Learning Models on EEG Data. - Maria Trigka; Elias Dritsas; Phivos Mylonas (SETN, 2024)

Performance and Security Analysis of the Diffie-Hellman Key Exchange Protocol. - Elias Dritsas; Maria Trigka; Phivos Mylonas (SMAP, 2024)

Application of Machine Learning Models to Predict e-Learning Engagement Using EEG Data. - Elias Dritsas; Maria Trigka; Phivos Mylonas (WEBIST, 2024)

Utilizing Multi-Class Classification Methods for Automated Sleep Disorder Prediction. - Elias Dritsas; Maria Trigka (Inf., 2024)

Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey. - Elias Dritsas; Maria Trigka (Future Internet, 2024)

Application of Deep Learning for Heart Attack Prediction with Explainable Artificial Intelligence. - Elias Dritsas; Maria Trigka (Comput., 2024)

Applying Machine Learning on Big Data With Apache Spark. - Elias Dritsas; Maria Trigka (IEEE Access, 2025)

Database Systems in the Big Data Era: Architectures, Performance, and Open Challenges. - Elias Dritsas; Maria Trigka (IEEE Access, 2025)

Machine Learning in E-Commerce: Trends, Applications, and Future Challenges. - Elias Dritsas; Maria Trigka (IEEE Access, 2025)

Machine Learning in Intelligent Networks: Architectures, Techniques, and Use Cases. - Elias Dritsas; Maria Trigka (IEEE Access, 2025)

Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions. - Elias Dritsas; Maria Trigka (IEEE Access, 2025)

Improving Cardiovascular Disease Prediction With Deep Learning and Correlation-Aware SMOTE. - Maria Trigka; Elias Dritsas (IEEE Access, 2025)

Wireless Sensor Networks: From Fundamentals and Applications to Innovations and Future Trends. - Maria Trigka; Elias Dritsas (IEEE Access, 2025)

The Evolution of Generative AI: Trends and Applications. - Maria Trigka; Elias Dritsas (IEEE Access, 2025)

A Survey on Cybersecurity in IoT. - Elias Dritsas; Maria Trigka (Future Internet, 2025)

Edge and Cloud Computing in Smart Cities. - Maria Trigka; Elias Dritsas (Future Internet, 2025)

Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications. - Elias Dritsas; Maria Trigka (J. Sens. Actuator Networks, 2025)

Exploring the Intersection of Machine Learning and Big Data: A Survey. - Elias Dritsas; Maria Trigka (Mach. Learn. Knowl. Extr., 2025)

Multimodal Interaction, Interfaces, and Communication: A Survey. - Elias Dritsas; Maria Trigka; Christos Troussas; Phivos Mylonas (Multimodal Technol. Interact., 2025)