Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Pierluigi Salvo Rossi"'
Publikováno v:
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Background The use of machine learning is becoming increasingly popular in many disciplines, but there is still an implementation gap of machine learning models in clinical settings. Lack of trust in models is one of the issues that need to
Externí odkaz:
https://doaj.org/article/7ab1413b97684739828f6330231e303c
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-14 (2022)
Abstract Background Machine learning (ML) holds the promise of becoming an essential tool for utilising the increasing amount of clinical data available for analysis and clinical decision support. However, the lack of trust in the models has limited
Externí odkaz:
https://doaj.org/article/b53395cc54704e2f852efd17ce61fd45
Publikováno v:
Sensors, Vol 23, Iss 5, p 2844 (2023)
The recent wave of digitalization is characterized by the widespread deployment of sensors in many different environments, e.g., multi-sensor systems represent a critical enabling technology towards full autonomy in industrial scenarios. Sensors usua
Externí odkaz:
https://doaj.org/article/92f79bf993df486380f6d26efe070f66
Publikováno v:
Energies, Vol 15, Iss 17, p 6153 (2022)
Increased renewable energy production and storage is a key pillar of net-zero emission. The expected growth in the exploitation of offshore renewable energy sources, e.g., wind, provides an opportunity for decarbonising offshore assets and mitigating
Externí odkaz:
https://doaj.org/article/f54a72de505c411c954fb06d28b4f334
Publikováno v:
Chemical Engineering Transactions, Vol 82 (2020)
The use of Wireless Sensor Networks (WSNs) in support of Dynamic Risk Assessment regarding oil spills still lacks a proper integration. WSNs enable prompt responses to such emergencies through an appropriate inspection, thus avoiding possible larger
Externí odkaz:
https://doaj.org/article/4c1a82e411364bc79f20cf9616f40926
Publikováno v:
Remote Sensing, Vol 13, Iss 19, p 3938 (2021)
In a low-angle tracking situation, estimating the elevation angle is challenging due to the entrance of the multipath signals in the antenna’s main lobe. In this article, we propose two methods based on the extended Kalman filter (EKF) and frequenc
Externí odkaz:
https://doaj.org/article/87eda75058b948539d9927e66ed1acd5
Publikováno v:
Remote Sensing, Vol 13, Iss 8, p 1486 (2021)
Underwater source localization is an important task, especially for real-time operation. Recently, machine learning methods have been combined with supervised learning schemes. This opens new possibilities for underwater source localization. However,
Externí odkaz:
https://doaj.org/article/3b3c998bc0404e999a69818b8632a566
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
13299-13308
IEEE Sensors Journal
IEEE Sensors Journal
We propose a time-frequency fused underwater acoustic source localization method based on self-supervised learning with contrastive predictive coding. Firstly, two feature extractors are trained to solve the pretext task (predicting the future) based
Autor:
Marcello Zappia, Domenico Albano, Alberto Aliprandi, Antonio Barile, Luca Brunese, Alessandro Castagna, Andrea Cozzolino, Massimo De Filippo, Francesco Di Pietto, Mariano Giuseppe Di Salvatore, Eugenio Annibale Genovese, Salvatore Guarino, Pasquale Guerriero, Giovanni Merolla, Carmelo Messina, Riccardo Ranieri, Alfonso Maria Romano, Raffaele Russo, Michele Tumminello, Pierluigi Salvo Rossi, Luca Maria Sconfienza, Vito Chianca
Purpose:The aim of this multicentric study was to assess which imaging method has the best inter-reader agreement for glenoid bone loss quantification in anterior shoulder instability. A further aim was to calculate the inter-method agreement compari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8237fb655f6b608a3f6473e3f397041b
https://hdl.handle.net/10447/578448
https://hdl.handle.net/10447/578448