| Dynamic graph convolutional networks F Manessi, A Rozza, M Manzo Pattern Recognition 97, 107000, 2020 | 342 | 2020 |
| Adjusted F-measure and kernel scaling for imbalanced data learning A Maratea, A Petrosino, M Manzo Information Sciences 257, 331-341, 2014 | 195 | 2014 |
| Graph Convolutional Networks: analysis, improvements and results I Ullah, M Manzo, M Shah, MG Madden Applied Intelligence, 1-12, 2021 | 38* | 2021 |
| Voting in Transfer Learning System for Ground-Based Cloud Classification M Manzo, S Pellino Machine Learning and Knowledge Extraction 3 (3), 542-553, 2021 | 27 | 2021 |
| Bucket of deep transfer learning features and classification models for melanoma detection M Manzo, S Pellino Journal of Imaging 6 (12), 129, 2020 | 26 | 2020 |
| Fighting together against the pandemic: Learning multiple models on tomography images for COVID-19 diagnosis M Manzo, S Pellino AI 2 (2), 261-273, 2021 | 21 | 2021 |
| A novel graph-based fisher kernel method for semi-supervised learning A Rozza, M Manzo, A Petrosino 2014 22nd International Conference on Pattern Recognition, 3786-3791, 2014 | 21 | 2014 |
| Netpro2vec: a graph embedding framework for biomedical applications I Manipur, M Manzo, I Granata, M Giordano, L Maddalena, MR Guarracino IEEE/ACM Transactions on Computational Biology and Bioinformatics 19 (2 …, 2021 | 19 | 2021 |
| Attributed relational sift-based regions graph for art painting retrieval M Manzo, A Petrosino Image Analysis and Processing–ICIAP 2013: 17th International Conference …, 2013 | 13 | 2013 |
| A novel graph embedding framework for object recognition M Manzo, S Pellino, A Petrosino, A Rozza European Conference on Computer Vision, 341-352, 2014 | 12 | 2014 |
| Attributed relational sift-based regions graph: Concepts and applications M Manzo Machine Learning and Knowledge Extraction 2 (3), 233-255, 2020 | 10* | 2020 |
| Graph-based image matching for indoor localization M Manzo Machine Learning and Knowledge Extraction 1 (3), 46, 2019 | 10 | 2019 |
| Adversarial attacks on graph-level embedding methods: A case study M Giordano, L Maddalena, M Manzo, MR Guarracino Annals of Mathematics and Artificial Intelligence 91 (2), 259-285, 2023 | 9 | 2023 |
| Automatic Generation of SCORM Complaint Metadata for Portable Document Format Files A Maratea, A Petrosino, M Manzo International Conference on Computer Systems and Technologies 2012, 2012 | 9 | 2012 |
| Whole-graph embedding and adversarial attacks for life sciences L Maddalena, M Giordano, M Manzo, MR Guarracino International Symposium on Mathematical and Computational Biology, 1-21, 2021 | 8 | 2021 |
| On whole-graph embedding techniques L Maddalena, I Manipur, M Manzo, MR Guarracino Trends in Biomathematics: Chaos and Control in Epidemics, Ecosystems, and …, 2021 | 8 | 2021 |
| Learning from metabolic networks: current trends and future directions for precision medicine I Granata, M Manzo, A Kusumastuti, MR Guarracino Current medicinal chemistry, 2020 | 8 | 2020 |
| Glioma Grade Classification via Omics Imaging L Maddalena, I Granata, I Manipur, M Manzo, M Guarracino 13th International Joint Conference on Biomedical Engineering Systems and …, 2020 | 8 | 2020 |
| Extended graph backbone for motif analysis A Maratea, A Petrosino, M Manzo Proceedings of the 18th International Conference on Computer Systems and …, 2017 | 8 | 2017 |
| Triadic motifs in the partitioned world trade web A Maratea, A Petrosino, M Manzo Procedia Computer Science 98, 479-484, 2016 | 8 | 2016 |
Alfredo PetrosinoUniversity of Naples ParthenopeПодтвержден адрес электронной почты в домене uniparthenope.it
