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https://rd.uffs.edu.br/handle/prefix/9168Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.contributor.advisor1 | Feitosa, Samuel da Silva | - |
| dc.contributor.advisor-co1 | Lima, Julyane Felipette | - |
| dc.creator | Penha, Cecília de Oliveira | - |
| dc.date | 2025-12-11 | - |
| dc.date.accessioned | 2026-03-25T13:18:09Z | - |
| dc.date.available | 2026 | - |
| dc.date.available | 2026-03-25T13:18:09Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.uri | https://rd.uffs.edu.br/handle/prefix/9168 | - |
| dc.description.resumo | When treating skin lesions, accurate assessment of wound healing re- mains a challenge for health professionals. Precise estimation of the wound area is required to determine if the current approach is efficient or if a new interven- tion is required. This paper proposes a study on the ability of computer vision algorithms and deep learning networks to measure the size of dermatological wounds based on images. By employing an approach based on the U-Net archi- tecture, the study evaluates the model’s ability to segment wounds and provide area estimations. Results demonstrate that the proposed method can support decision making by health professionals by offering consistent measurements, contributing to faster and efficient patient care. | pt_BR |
| dc.description.provenance | Submitted by Biblioteca Chapeco (biblio.ch@uffs.edu.br) on 2026-03-24T15:55:37Z No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5) | en |
| dc.description.provenance | Approved for entry into archive by DIONE ROSSI FARIAS (dione@uffs.edu.br) on 2026-03-25T13:18:09Z (GMT) No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5) | en |
| dc.description.provenance | Made available in DSpace on 2026-03-25T13:18:09Z (GMT). No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5) Previous issue date: 2025 | en |
| dc.language | por | pt_BR |
| dc.publisher | Universidade Federal da Fronteira Sul | pt_BR |
| dc.publisher.country | Brasil | pt_BR |
| dc.publisher.department | Campus Chapecó | pt_BR |
| dc.publisher.initials | UFFS | pt_BR |
| dc.rights | Acesso Aberto | pt_BR |
| dc.subject | Aprendizagem profunda | pt_BR |
| dc.subject | Inteligência artificial | pt_BR |
| dc.subject | Doenças da pele e do tecido conjuntivo | pt_BR |
| dc.subject | Ferimentos e lesões | pt_BR |
| dc.subject | Processamento de imagens | pt_BR |
| dc.title | Applications of deep learning to measure skin lesions | pt_BR |
| dc.type | Monografia | pt_BR |
| Aparece en las colecciones: | Ciência da Computação | |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| PENHA.pdf | 1.34 MB | Adobe PDF | Visualizar/Abrir |
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