Detection of retinal anatomical structures and its application to image quality assessment (2025)
- Authors:
- USP affiliated authors: HIRATA, NINA SUMIKO TOMITA - IME ; MICHELASSI, RODRIGO DE CASTRO - IME
- Unidade: IME
- DOI: 10.5753/sibgrapi.est.2025.38309
- Subjects: PROCESSAMENTO DE IMAGENS; IMAGEM DIGITAL; RETINA; TÉCNICAS DE DIAGNÓSTICO OFTALMOLÓGICO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2025
- Source:
- Título: Anais Estendidos
- Conference titles: Workshop de Trabalhos da Graduação - Conference on Graphics, Patterns, and Images - SIBGRAPI
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
MICHELASSI, Rodrigo de Castro e HIRATA, Nina Sumiko Tomita. Detection of retinal anatomical structures and its application to image quality assessment. 2025, Anais.. Porto Alegre: SBC, 2025. Disponível em: https://sol.sbc.org.br/index.php/sibgrapi_estendido/article/view/38309/38083. Acesso em: 21 jan. 2026. -
APA
Michelassi, R. de C., & Hirata, N. S. T. (2025). Detection of retinal anatomical structures and its application to image quality assessment. In Anais Estendidos. Porto Alegre: SBC. doi:10.5753/sibgrapi.est.2025.38309 -
NLM
Michelassi R de C, Hirata NST. Detection of retinal anatomical structures and its application to image quality assessment [Internet]. Anais Estendidos. 2025 ;[citado 2026 jan. 21 ] Available from: https://sol.sbc.org.br/index.php/sibgrapi_estendido/article/view/38309/38083 -
Vancouver
Michelassi R de C, Hirata NST. Detection of retinal anatomical structures and its application to image quality assessment [Internet]. Anais Estendidos. 2025 ;[citado 2026 jan. 21 ] Available from: https://sol.sbc.org.br/index.php/sibgrapi_estendido/article/view/38309/38083 - A comparative study on few-shot learning for retinal disease classification
- Subexpression and dominant symbol histograms for spatial relation classification in mathematical expressions
- Ferramenta interativa de desenho de redes de regulação gênica
- The use of high resolution images in morphological operator learning
- Morphological operator design from training data
- Automatic labeling of handwritten mathematical symbols via expression matching
- Fast QR code detection in arbitrarily acquired images
- Image operator learning coupled with CNN classification and its application to staff line removal
- Binary image operator design based on stacked generalization
- Projeto automático de operadores: explorando conhecimentos a priori
Informações sobre o DOI: 10.5753/sibgrapi.est.2025.38309 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
