Reinforcement learning for personalization: a systematic literature review F den Hengst, EM Grua, A el Hassouni, M Hoogendoorn | 50 | 2020 |
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 | 35 | 2020 |
Self-Adaptation in Mobile Apps: a Systematic Literature Study EM Grua, I Malavolta, P Lago SEAMS 2019, 2019 | 31 | 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, ... | 28 | 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 | 18 | 2018 |
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 | 17 | 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 | 16 | 2020 |
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 | 15 | 2023 |
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 | 15 | 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 | 14 | 2022 |
Modelling and predicting User Engagement in mobile applications E Barbaro, EM Grua, I Malavolta, M Stercevic, E Weusthof, ... Data Science, 1-17, 2019 | 14 | 2019 |
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 | 11 | 2021 |
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 | 6 | 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 | 6 | 2023 |
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 | 4 | 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 | 4 | 2022 |
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 | 2 | 2024 |
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 | 1 | 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 | | 2024 |
The Future of E-Health is Mobile: Combining AI and Self-Adaptation to Create Adaptive E-Health Mobile Applications EM Grua | | 2021 |