| Machine Learning approach for Predictive Maintenance in Industry 4.0 M Paolanti, L Romeo, A Felicetti, A Mancini, E Frontoni, J Loncarski 2018 14th IEEE/ASME International Conference on Mechatronic and Embedded …, 2018 | 242 | 2018 |
| A sequential deep learning application for recognising human activities in smart homes D Liciotti, M Bernardini, L Romeo, E Frontoni Neurocomputing 396, 501-513, 2020 | 160 | 2020 |
| Real-time mental stress detection based on smartwatch L Ciabattoni, F Ferracuti, S Longhi, L Pepa, L Romeo, F Verdini 2017 IEEE International Conference on Consumer Electronics (ICCE), 110-111, 2017 | 118 | 2017 |
| Harnessing the power of smart and connected health to tackle covid-19: Iot, ai, robotics, and blockchain for a better world F Firouzi, B Farahani, M Daneshmand, K Grise, J Song, R Saracco, ... IEEE Internet of Things Journal 8 (16), 12826-12846, 2021 | 111 | 2021 |
| SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0 M Calabrese, M Cimmino, F Fiume, M Manfrin, L Romeo, S Ceccacci, ... Information 11 (4), 202, 2020 | 111 | 2020 |
| Discovering the type 2 diabetes in electronic health records using the sparse balanced support vector machine M Bernardini, L Romeo, P Misericordia, E Frontoni IEEE Journal of Biomedical and Health Informatics 24 (1), 235-246, 2019 | 101 | 2019 |
| The KIMORE Dataset: KInematic Assessment of MOvement and Clinical Scores for Remote Monitoring of Physical REhabilitation M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, A Monteriù, L Romeo, ... IEEE Transactions on Neural Systems and Rehabilitation Engineering 27 (7 …, 2019 | 95 | 2019 |
| Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0 L Romeo, J Loncarski, M Paolanti, G Bocchini, A Mancini, E Frontoni Expert Systems with Applications 140, 112869, 2020 | 90 | 2020 |
| From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0 R Rosati, L Romeo, G Cecchini, F Tonetto, P Viti, A Mancini, E Frontoni Journal of Intelligent Manufacturing 34 (1), 107-121, 2023 | 78 | 2023 |
| A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation A Monteriù, M Prist, E Frontoni, S Longhi, F Pietroni, S Casaccia, ... Sensors 18 (7), 2310, 2018 | 64 | 2018 |
| Accuracy evaluation of the kinect v2 sensor during dynamic movements in a rehabilitation scenario M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, S Longhi, L Romeo, ... 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 61 | 2016 |
| A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment M Capecci, MG Ceravolo, F Ferracuti, S Iarlori, V Kyrki, A Monteriu, ... Journal of biomedical informatics 78, 1-11, 2018 | 57 | 2018 |
| Robotic retail surveying by deep learning visual and textual data M Paolanti, L Romeo, M Martini, A Mancini, E Frontoni, P Zingaretti Robotics and Autonomous Systems 118, 179-188, 2019 | 48 | 2019 |
| Faster R-CNN approach for detection and quantification of DNA damage in comet assay images R Rosati, L Romeo, S Silvestri, F Marcheggiani, L Tiano, E Frontoni Computers in Biology and Medicine 123, 103912, 2020 | 45 | 2020 |
| Multiple instance learning for emotion recognition using physiological signals L Romeo, A Cavallo, L Pepa, N Bianchi-Berthouze, M Pontil IEEE Transactions on Affective Computing 13 (1), 389-407, 2019 | 41 | 2019 |
| Early temporal prediction of type 2 diabetes risk condition from a general practitioner electronic health record: A multiple instance boosting approach M Bernardini, M Morettini, L Romeo, E Frontoni, L Burattini Artificial Intelligence in Medicine 105, 101847, 2020 | 40 | 2020 |
| Measurement of Users’ Well-Being Through Domotic Sensors and Machine Learning Algorithms S Casaccia, L Romeo, A Calvaresi, N Morresi, A Monteriù, E Frontoni, ... IEEE Sensors Journal 20 (14), 8029-8038, 2020 | 39 | 2020 |
| Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke P Sale, G Ferriero, L Ciabattoni, AM Cortese, F Ferracuti, L Romeo, ... Journal of Stroke and Cerebrovascular Diseases 27 (11), 2962-2972, 2018 | 36 | 2018 |
| A Unified Hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign L Romeo, E Frontoni Pattern Recognition 121, 108197, 2022 | 34 | 2022 |
| Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients J Montomoli, L Romeo, S Moccia, M Bernardini, L Migliorelli, D Berardini, ... Journal of Intensive Medicine 1 (02), 110-116, 2021 | 34 | 2021 |
Emanuele FrontoniFull Professor of Computer Engineering UNIMC & co-director VRAI Lab在 unimc.it 的电子邮件经过验证
