Zobrazeno 1 - 10 of 15 pro vyhledávání: '"Manuel Emilio Gegúndez Arias"'
1
Empirical models of the solar field in concentrated solar thermal plants. An application to scheduling
Autor: Emilian Gelu Cojocaru, Manuel Emilio Gegúndez-Arias, José Manuel Bravo Caro, Manuel Jesús Vasallo
Publikováno v: Gegundez Arias, Manuel_E.
RUC. Repositorio da Universidade da Coruña
instname
[Resumen] Uno de los bloques fundamentales de una planta termosolar de concentración es el campo solar. En este bloque, la energía del recurso solar se captura y concentra sobre un fluido para su posterior utilización como energía térmica. La es
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f3e6cda539fe224ed254780b3799450
https://doi.org/10.17979/spudc.9788497497169.466
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2
A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model
Autor: Isaac Perez-Borrero, Manuel J. Vasallo-Vazquez, Manuel Emilio Gegúndez-Arias, Diego Marin-Santos
Publikováno v: Computer methods and programs in biomedicine. 205
Background and Objective: Automatic monitoring of retinal blood vessels proves very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This paper presents an efficient and accurate deep learning-based method for vessel
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f0ed5ab3a5ef4fd45982ff670c48f30
https://pubmed.ncbi.nlm.nih.gov/33882418
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4
A fast and accurate deep learning method for strawberry instance segmentation
Autor: Isaac Perez-Borrero, Manuel Emilio Gegúndez-Arias, Diego Marin-Santos, Estefanía Cortés-Ancos
Publikováno v: Computers and Electronics in Agriculture. 178:105736
Fruit instance segmentation is a key element for autonomous picking systems. This paper proposes a methodology for instance segmentation of strawberries using deep learning techniques. This methodology presents the following changes in relation to th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2b48c8d829f6f4506b2d5c523e7b9477
https://doi.org/10.1016/j.compag.2020.105736
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5
An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification
Autor: Javier Garrido, Diego Marin, José Manuel Bravo, Manuel Emilio Gegúndez-Arias, Carlos Ortega, Manuel Jesús Vasallo, Beatriz Ponte, Fatima Alvarez
Publikováno v: Medicalbiological engineeringcomputing. 56(8)
The present paper aims at presenting the methodology and first results of a detection system of risk of diabetic macular edema (DME) in fundus images. The system is based on the detection of retinal exudates (Ex), whose presence in the image is clini
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9147b21cf98d1c2f0394e56b6967ae9c
https://pubmed.ncbi.nlm.nih.gov/29318442
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6
A tool for automated diabetic retinopathy pre-screening based on retinal image computer analysis
Autor: Fatima Alvarez, Carlos Ortega, Manuel Jesús Vasallo, Diego Marin, Manuel Emilio Gegúndez-Arias, Javier Garrido, José Manuel Bravo, Beatriz Ponte
Publikováno v: Computers in biology and medicine. 88
AimThis paper presents a methodology and first results of an automatic detection system of first signs of Diabetic Retinopathy (DR) in fundus images, developed for the Health Ministry of the Andalusian Regional Government (Spain). Material and method
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7620312dfa83a3c98a97d688ed8af46
https://pubmed.ncbi.nlm.nih.gov/28711766
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7
Microaneurysm Candidate Extraction Methodology in Retinal Images for the Integration into Classification-Based Detection Systems
Autor: Manuel Emilio Gegúndez-Arias, Diego Marin, Estefanía Cortés-Ancos
Publikováno v: Bioinformatics and Biomedical Engineering ISBN: 9783319561479
IWBBIO (1)
Diabetic Retinopathy (DR) is one of the most common complications of long-term diabetes. It is a progressive disease that causes retina damage. DR is asymptomatic at the early stages and can lead to blindness if it is not treated in time. Thus, patie
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7561b9f2647dae8f46ddab530ca68dce
https://doi.org/10.1007/978-3-319-56148-6_33
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8
Planificación de la producción basada en control predictivo para plantas termosolares
Autor: José Manuel Bravo Caro, Manuel Jesús Vasallo Vázquez, Emilian Gelu Cojocaru, Manuel Emilio Gegúndez Arias
Publikováno v: Gegundez Arias, Manuel_E.
RUC. Repositorio da Universidade da Coruña
instname
RUC: Repositorio da Universidade da Coruña
Universidade da Coruña (UDC)
RUO. Repositorio Institucional de la Universidad de Oviedo
[Resumen] Se presenta una estrategia basada en control predictivo para resolver la planificación de la producción en plantas termosolares con almacenamiento térmico participando en el mercado diario de electricidad. Mediante esta estrategia, la pr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c2f40d06c20b2335b66433fd2ac5774
https://hdl.handle.net/2183/25898
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9
Inter-observer Reliability and Agreement Study on Early Diagnosis of Diabetic Retinopathy and Diabetic Macular Edema Risk
Autor: Manuel Emilio Gegúndez-Arias, Fatima Alvarez, Carlos Ortega, Diego Marin, Beatriz Ponte, Javier Garrido
Publikováno v: Bioinformatics and Biomedical Engineering ISBN: 9783319317434
IWBBIO
The degree of inter-observer agreement on early diagnosis of diabetic retinopathy (DR) and diabetic macular edema (DME) risk has been assessed in this paper. Three sets of DR and DME risk ratings on 529 diabetic patients were independently built by o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6bb0dbe016665932e0061521214285bd
https://doi.org/10.1007/978-3-319-31744-1_33
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10
Automated Detection of Diabetic Macular Edema Risk in Fundus Images
Autor: Manuel Emilio Gegúndez-Arias, Fatima Alvarez, Javier Garrido, Beatriz Ponte, Carlos Ortega, Diego Marin
Publikováno v: Bioinformatics and Biomedical Engineering ISBN: 9783319317434
IWBBIO
This paper is aimed at assessing the initial performance of a computer-based system to detect the risk of diabetic macular edema (DME). The development of this tool was funded by the Health Ministry of the Andalusian Regional Government (Spain) with
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c7a7df1e812dfdc2f23c349d0294a5ed
https://doi.org/10.1007/978-3-319-31744-1_34
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