Eoin Martino Grua
Eoin Martino Grua
Assistant Professor, University of Limerick
Preverjeni e-poštni naslov na ul.ie - Domača stran
Reinforcement learning for personalization: a systematic literature review
F den Hengst, EM Grua, A el Hassouni, M Hoogendoorn
A framework for the automatic execution of measurement-based experiments on Android devices
I Malavolta, EM Grua, CY Lam, R De Vries, F Tan, E Zielinski, M Peters, ...
Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020
Self-Adaptation in Mobile Apps: a Systematic Literature Study
EM Grua, I Malavolta, P Lago
SEAMS 2019, 2019
Investigating the correlation between performance scores and energy consumption of mobile web apps
K Chan-Jong-Chu, T Islam, MM Exposito, S Sheombar, C Valladares, ...
Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing
EM Grua, M Hoogendoorn
2018 IEEE Symposium Series on Computational Intelligence (SSCI), 813-820, 2018
A Reference Architecture for Personalized and Self-adaptive e-Health Apps
EM Grua, M De Sanctis, P Lago
Software Architecture: 14th European Conference, {ECSA} 2020 Tracks and …, 2020
Towards a sustainable business model for smartphones: Combining product-service systems with modularity.
AF Schneider, S Matinfar, EM Grua, D Casado-Mansilla, L Cordewener
ICT4S, 82-99, 2018
CluStream-GT: Online Clustering for Personalization in the Health Domain
EM Grua, M Hoogendoorn, I Malavolta, P Lago, AE Eiben
IEEE/WIC/ACM International Conference on Web Intelligence, 270-275, 2019
Modelling and predicting User Engagement in mobile applications
E Barbaro, EM Grua, I Malavolta, M Stercevic, E Weusthof, ...
Data Science, 1-17, 2019
An evaluation of the effectiveness of personalization and self-adaptation for e-Health apps
EM Grua, M De Sanctis, I Malavolta, M Hoogendoorn, P Lago
Information and Software Technology, 106841, 2022
Social Sustainability in the e-Health Domain via Personalized and Self-Adaptive Mobile Apps
EM Grua, MD Sanctis, I Malavolta, M Hoogendoorn, P Lago
Software Sustainability, 301-328, 2021
Quantifying the Effects of Ground Truth Annotation Quality on Object Detection and Instance Segmentation Performance
C Agnew, C Eising, P Denny, A Scanlan, P Van De Ven, EM Grua
IEEE Access, 2023
Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenge
D Jakab, BM Deegan, S Sharma, EM Grua, J Horgan, E Ward, ...
arXiv preprint arXiv:2402.12041, 2024
Detecting the Overfilled Status of Domestic and Commercial Bins using Computer Vision
C Agnew, D Mewada, EM Grua, C Eising, P Denny, M Heffernan, ...
Intelligent Systems with Applications, 200229, 2023
Other PHQ-9 item pairings are better than the PHQ-2: A Machine Learning analysis
D Glavin, E Maekawa, EM Grua, CA Nakamura, M Scazufca, R Araya, ...
Procedia Computer Science 206, 101-110, 2022
Bayesian networks for feature selection and patient pre-screening for depressive symptomatology: a prototype
E Maekawa, EM Grua, CA Nakamura, M Scazufca, R Araya, TJ Peters, ...
Journal of Medical Internet Research Mental Health, 2024
Measuring Natural Scenes SFR of Automotive Fisheye Cameras
D Jakab, EM Grua, BM Deegan, A Scanlan, P Van De Ven, C Eising
arXiv preprint arXiv:2401.05232, 2024
Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis
D Glavin, EM Grua, CA Nakamura, M Scazufca, ER Dos Santos, ...
JMIR Mental Health 10 (1), e48444, 2023
A Machine Learning approach to optimize the assessment of depressive symptomatology
M Eduardo, G Darragh, GE Martino, NC Akemi, S Marcia, A Ricardo
Procedia Computer Science 206, 111-120, 2022
The Future of E-Health is Mobile: Combining AI and Self-Adaptation to Create Adaptive E-Health Mobile Applications
EM Grua
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