Zobrazeno 1 - 5 of 5 pro vyhledávání: '"Diogo A.P. Nunes"'
1
Akademický článek
Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies
Autor: Joel Santos, Diogo A.P. Nunes, Ruslan Padnevych, José Carlos Quaresma, Martim Lopes, Joana Gil, João Pedro Bernardes, Tania Manuel Casimiro
Publikováno v: Science and Technology of Archaeological Research, Vol 10, Iss 1 (2024)
This article presents a novel approach to classifying archaeological artefacts using machine learning, specifically deep learning, rather than relying on traditional, time-consuming human-based methods. By employing Convolutional Neural Networks (CNN
Externí odkaz: https://doaj.org/article/a0a2c8eb40c649588d3a4ddd25ef9722
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2
Akademický článek
Analysis of chronic pain descriptions for base-pathology prediction: the case of rheumatoid arthritis versus spondylitis pathology prediction based on pain descriptions
Autor: Diogo A.P. Nunes, Joana Ferreira-Gomes, Carlos Vaz, Daniela Oliveira, Sofia Pimenta, Fani Neto, David Martins de Matos
Publikováno v: Revista Dor, Vol 28, Iss 2 (2021)
The language of pain is a sub-language used to describe a subjective, private, and painful experience. In the clinical assessment and management of chronic pain, which is not as straightforward as acute pain, verbal communication is key to convey rel
Externí odkaz: https://doaj.org/article/b3a542389d1142c793a58434dee9d6be
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4
Chronic pain patient narratives allow for the estimation of current pain intensity
Autor: Diogo A.P. Nunes, Joana Ferreira-Gomes, Daniela Oliveira, Carlos Vaz, Sofia Pimenta, Fani Neto, David Martins de Matos
Chronic pain is a multi-dimensional experience, and pain intensity plays an important part, impacting the patients emotional balance, psychology, and behaviour. Standard self-reporting tools, such as the Visual Analogue Scale for pain, fail to captur
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68b7a7eb6bf6ca5f89547969ab17c606
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5
Akademický článek
Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies.
Autor: Santos, Joel1 (AUTHOR) joelrosantos@gmail.com, Nunes, Diogo A.P.2 (AUTHOR), Padnevych, Ruslan3 (AUTHOR), Quaresma, José Carlos4 (AUTHOR), Lopes, Martim4 (AUTHOR), Gil, Joana5 (AUTHOR), Bernardes, João Pedro6,7 (AUTHOR), Casimiro, Tania Manuel8 (AUTHOR)
Publikováno v: Science & Technology of Archaeological Research. Dec2024, Vol. 10 Issue 1, p1-17. 17p.
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