ZOPPIS ITALO FRANCESCO

Lazzarinetti, G., Dondi, R., Manzoni, S., Zoppis, I. (2025). DLMinTC+: A Deep Learning Based Algorithm for Minimum Timeline Cover on Temporal Graphs. ALGORITHMS, 18(2) [10.3390/a18020113]. Detail

Lazzarinetti, G., Manzoni, S., Zoppis, I. (2025). Automating Resume Analysis: Knowledge Graphs via Prompt Engineering. In AIxIA 2024 – Advances in Artificial Intelligence XXIIIrd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2024, Bolzano, Italy, November 25–28, 2024 Proceedings (pp.214-227). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-80607-0_17]. Detail

Zancanaro, A., Cisotto, G., Zoppis, I., Manzoni, S. (2024). vEEGNet: Learning Latent Representations to Reconstruct EEG Raw Data via Variational Autoencoders. In M. Ziefle, M.D. Lozano, M. Mulvenna (a cura di), Information and Communication Technologies for Ageing Well and e-Health
9th International Conference, ICT4AWE 2023, Prague, Czech Republic, April 22–24, 2023, Revised Selected Papers (pp. 114-129). Springer [10.1007/978-3-031-62753-8_7]. Detail

Cisotto, G., Tegegn, D., Zancanaro, A., Reguzzoni, I., Lotti, E., Manzoni, S., et al. (2024). An AI-empowered energy-efficient portable NIRS solution for precision agriculture: A pilot study on a citrus fruit. In Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS) (pp.313-318). Institute of Electrical and Electronics Engineers Inc. [10.15439/2024F5111]. Detail

Cisotto, G., Zancanaro, A., Zoppis, I., Manzoni, S. (2024). hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction. FRONTIERS IN NEUROINFORMATICS, 18 [10.3389/fninf.2024.1459970]. Detail