Davide Piccinini

Argomento di ricerca

My work focuses on remote sensing applications and deployment of deep learning techniques.

Tutori

• Enrico Magli
• Diego Valsesia

Corso di laurea magistrale

• Machine learning and neural networks. A.A. 2026/27, ICT ENGINEERING FOR SMART SOCIETIES. Collaboratore del corso

• Impieri, M.; Piccinini, D.; Valsesia, D.; Magli, E. (2026)
  Onboard Real-Time Hyperspectral Subpixel Mapping With Pushbroom Neural Network. In: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, vol. 19, pp. 17403-17419. ISSN 1939-1404
  Contributo su Rivista
• Yi, Z.; Piccinini, D.; Valsesia, D.; Bianchi, T.; Magli, E. (2026)
  Scalable Neural Pushbroom Architectures for Real-Time Denoising of Hyperspectral Images Onboard Satellites. In: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 64. ISSN 0196-2892
  Contributo su Rivista
• Piccinini, Davide; Valsesia, Diego; Magli, Enrico (2025)
  Towards Deep Line-Based Architectures for Onboard Hyperspectral Image Super-Resolution. In: IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium, Brisbane (Aus), 03-08 August 2025, pp. 6241-6245. ISBN: 979-8-3315-0810-4
  Contributo in Atti di Convegno (Proceeding)
• Piccinini, D.; Valsesia, D.; Magli, E. (2025)
  Onboard Hyperspectral Super-Resolution with Deep Pushbroom Neural Network †. In: REMOTE SENSING, vol. 17. ISSN 2072-4292
  Contributo su Rivista
• Magli, E; Angarano, S.; Bassetti, S.; Bianchi, T.; Boccardo, P.; Bucci, S.; Chiaberge, ... (2024)
  A multi-service edge-AI architecture based on self-supervised learning. In: 75th International Astronautical Congress, Milan (Ita), 14-18 October 2024, pp. 1-9
  Contributo in Atti di Convegno (Proceeding)