CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From the State-of-The-Art to DynamicNet. - Alberto Zancanaro; Giulia Cisotto; João Ruivo Paulo; Gabriel Pires; Urbano J. Nunes (CIBCB, 2021)

Impact of Transmission Delays Over Age of Information Under Finite Horizon Scheduling. - Alberto Zancanaro; Giulia Cisotto; Andrea Munari; Leonardo Badia (CAMAD, 2023)

vEEGNet: A New Deep Learning Model to Classify and Generate EEG. - Alberto Zancanaro; Italo Francesco Zoppis; Sara Manzoni; Giulia Cisotto (ICT4AWE, 2023)

hvEEGNet: exploiting hierarchical VAEs on EEG data for neuroscience applications. - Giulia Cisotto; Alberto Zancanaro; Italo Francesco Zoppis; Sara L. Manzoni (CoRR, 2023)

vEEGNet: learning latent representations to reconstruct EEG raw data via variational autoencoders. - Alberto Zancanaro; Giulia Cisotto; Italo Zoppis; Sara Lucia Manzoni (CoRR, 2023)

Modeling Value of Information in remote sensing from correlated sources. - Alberto Zancanaro; Giulia Cisotto; Leonardo Badia (Comput. Commun., 2023)

Tackling Age of Information in Access Policies for Sensing Ecosystems. - Alberto Zancanaro; Giulia Cisotto; Leonardo Badia (Sensors, 2023)

The Impact of Mis-Labeled Artefacts on Deep Learning Models for EEG Analysis: a Case Study. - Alberto Zancanaro; Giulia Cisotto (CIBB, 2024)

An AI-empowered energy-efficient portable NIRS solution for precision agriculture: A pilot study on a citrus fruit. - Giulia Cisotto; Tegegn Dagmawi Delelegn; Alberto Zancanaro; Ivan Reguzzoni; Edoardo Lotti; Sara L. Manzoni; Italo Francesco Zoppis (FedCSIS, 2024)

Status update scheduling in remote sensing under variable activation and propagation delays. - Leonardo Badia; Alberto Zancanaro; Giulia Cisotto; Andrea Munari (Ad Hoc Networks, 2024)

hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction. - Giulia Cisotto; Alberto Zancanaro; Italo Francesco Zoppis; Sara L. Manzoni (Frontiers Neuroinformatics, 2024)