Zobrazeno 1 - 10 of 45 pro vyhledávání: '"Antonios Papaleonidas"'
1
Akademický článek
COLAFOS: a hybrid machine learning model to forecast potential coseismic landslides severity
Autor: Anastasios Panagiotis Psathas, Antonios Papaleonidas, Lazaros Iliadis, George Papathanassiou, Sotirios Valkaniotis
Publikováno v: Journal of Information and Telecommunication, Vol 6, Iss 4, Pp 420-449 (2022)
Timely and rational prediction of coseismic landslides is crucial for the design and development of key infrastructure capable to protect human lives in seismically active regions. This research introduces the novel Hybrid Coseismic Landslide Forecas
Externí odkaz: https://doaj.org/article/663d87a1a41e4dae8a69edde2eb1b51d
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2
Akademický článek
High accuracy human activity recognition using machine learning and wearable devices’ raw signals
Autor: Antonios Papaleonidas, Anastasios Panagiotis Psathas, Lazaros Iliadis
Publikováno v: Journal of Information and Telecommunication, Vol 0, Iss 0, Pp 1-17 (2021)
Human activity recognition (HAR) is vital in a wide range of real-life applications such as health monitoring of olderly people, abnormal behaviour detection and smart home management. HAR systems can employ smart human-computer interfaces and be par
Externí odkaz: https://doaj.org/article/55facb38a4bf488ba8967f3251c30402
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4
High accuracy human activity recognition using machine learning and wearable devices’ raw signals
Autor: Lazaros Iliadis, Antonios Papaleonidas, Anastasios Panagiotis Psathas
Publikováno v: Journal of Information and Telecommunication, Vol 0, Iss 0, Pp 1-17 (2021)
Human activity recognition (HAR) is vital in a wide range of real-life applications such as health monitoring of olderly people, abnormal behaviour detection and smart home management. HAR systems can employ smart human-computer interfaces and be par
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36faa11da47dfc3befbb16221acf465b
https://doi.org/10.1080/24751839.2021.1987706
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10
An explanation-based approach for experiment reproducibility in recommender systems
Autor: Antonios Papaleonidas, Lazaros Iliadis, Nikolaos Polatidis, Elias Pimenidis
Publikováno v: Neural Computing and Applications. 32:12259-12266
The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error and the Root Mean Squared Error for error rating prediction and Precision and Recall for measuring the quality of the top-N recommend
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2b00fc9fce9bfd5ce3f312f5910570f4
https://doi.org/10.1007/s00521-019-04274-x
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