| Predictive modeling of pv energy production: How to set up the learning task for a better prediction? M Ceci, R Corizzo, F Fumarola, D Malerba, A Rashkovska IEEE Transactions on Industrial Informatics 13 (3), 956-966, 2017 | 121 | 2017 |
| Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification B Petrovska, E Zdravevski, P Lameski, R Corizzo, I Štajduhar, J Lerga Sensors 20 (14), 3906, 2020 | 110 | 2020 |
| The class imbalance problem in deep learning K Ghosh, C Bellinger, R Corizzo, P Branco, B Krawczyk, N Japkowicz Machine Learning 113 (7), 4845-4901, 2024 | 101 | 2024 |
| Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks J Kalajdjieski, E Zdravevski, R Corizzo, P Lameski, S Kalajdziski, IM Pires, ... Remote Sensing 12 (24), 4142, 2020 | 98 | 2020 |
| Multi-aspect renewable energy forecasting R Corizzo, M Ceci, H Fanaee-T, J Gama Information Sciences 546, 701-722, 2021 | 75 | 2021 |
| Spatial autocorrelation and entropy for renewable energy forecasting M Ceci, R Corizzo, D Malerba, A Rashkovska Data Mining and Knowledge Discovery 33 (3), 698-729, 2019 | 70 | 2019 |
| Anomaly detection and repair for accurate predictions in geo-distributed Big Data R Corizzo, M Ceci, N Japkowicz Big Data Research 16, 18-35, 2019 | 66 | 2019 |
| Scalable auto-encoders for gravitational waves detection from time series data R Corizzo, M Ceci, E Zdravevski, N Japkowicz Expert Systems with Applications 151, 113378, 2020 | 59 | 2020 |
| DENCAST: distributed density-based clustering for multi-target regression R Corizzo, G Pio, M Ceci, D Malerba Journal of Big Data 6 (1), 43, 2019 | 53 | 2019 |
| ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids M Ceci, R Corizzo, N Japkowicz, P Mignone, G Pio IEEE Access 8, 156053-156066, 2020 | 44 | 2020 |
| Aerial Scene Classification through Fine-Tuning with Adaptive Learning Rates and Label Smoothing B Petrovska, T Atanasova-Pacemska, R Corizzo, P Mignone, P Lameski, ... Applied Sciences 10 (17), 5792, 2020 | 44 | 2020 |
| Spark-GHSOM: Growing Hierarchical Self-Organizing Map for Large Scale Mixed Attribute Datasets A Malondkar, R Corizzo, I Kiringa, M Ceci, N Japkowicz Information Sciences 496, 572-591, 2019 | 39 | 2019 |
| Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning C Bellinger, R Corizzo, N Japkowicz International Conference on Discovery Science, 242-252, 2021 | 38* | 2021 |
| Multi-Horizon Air Pollution Forecasting with Deep Neural Networks M Arsov, E Zdravevski, P Lameski, R Corizzo, N Koteli, S Gramatikov, ... Sensors 21 (4), 1235, 2021 | 33 | 2021 |
| Big data techniques for supporting accurate predictions of energy production from renewable sources M Ceci, R Corizzo, F Fumarola, M Ianni, D Malerba, G Maria, E Masciari, ... Proceedings of the 19th International Database Engineering & Applications …, 2015 | 31 | 2015 |
| Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification B Krawczyk, C Bellinger, R Corizzo, N Japkowicz 2021 International Joint Conference on Neural Networks (IJCNN), 2021 | 29 | 2021 |
| Stock market prediction with time series data and news headlines: a stacking ensemble approach R Corizzo, J Rosen Journal of Intelligent Information Systems 62 (1), 27-56, 2024 | 26 | 2024 |
| Explainable image analysis for decision support in medical healthcare R Corizzo, Y Dauphin, C Bellinger, E Zdravevski, N Japkowicz 2021 IEEE International Conference on Big Data (Big Data), 4667-4674, 2021 | 25 | 2021 |
| Feature extraction based on word embedding models for intrusion detection in network traffic R Corizzo, E Zdravevski, M Russell, A Vagliano, N Japkowicz Journal of Surveillance, Security and Safety 1 (2), 140-150, 2020 | 25 | 2020 |
| WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data K Faber, R Corizzo, B Sniezynski, M Baron, N Japkowicz 2021 IEEE International Conference on Big Data (Big Data), 4450-4459, 2021 | 24 | 2021 |
Nathalie JapkowiczAmerican UniversityZweryfikowany adres z american.edu