izpis_h1_title_alt

Transfer learning with convolutional neuralnetworks for diabetic retinopathy image classification : a review
Kandel, Ibrahem (Avtor), Castelli, Mauro (Avtor)

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Izvleček
Diabetic retinopathy (DR) is a dangerous eye condition that affects diabetic patients. Without early detection, it can affect the retina and may eventually cause permanent blindness. The early diagnosis of DR is crucial for its treatment. However, the diagnosis of DR is a very difficult process that requires an experienced ophthalmologist. A breakthrough in the field of artificial intelligence called deep learning can help in giving the ophthalmologist a second opinion regarding the classification of the DR by using an autonomous classifier. To accurately train a deep learning model to classify DR, an enormous number of images is required, and this is an important limitation in the DR domain. Transfer learning is a technique that can help in overcoming the scarcity of images. The main idea that is exploited by transfer learning is that a deep learning architecture, previously trained on non-medical images, can be fine-tuned to suit the DR dataset. This paper reviews research papers that focus on DR classification by using transfer learning to present the best existing methods to address this problem. This review can help future researchers to find out existing transfer learning methods to address the DR classification task and to show their differences in terms of performance.

Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.02 - Pregledni znanstveni članek
Organizacija:EF - Ekonomska fakulteta
Leto izida:2020
Št. strani:str. 1-24
Številčenje:Vol. 10, iss. 6 (art. 2021)
UDK:004:78
ISSN pri članku:2076-3417
DOI:10.3390/app10062021 Povezava se odpre v novem oknu
COBISS.SI-ID:38420483 Povezava se odpre v novem oknu
Licenca:CC BY 4.0
To delo je dosegljivo pod licenco Creative Commons Priznanje avtorstva 4.0 Mednarodna
Število ogledov:23
Število prenosov:8
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
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Gradivo je del revije

Naslov:Applied sciences
Skrajšan naslov:Appl. sci.
Založnik:MDPI
ISSN:2076-3417
COBISS.SI-ID:522979353 Povezava se odpre v novem oknu

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:P5-0410
Naslov:Digitalizacija kot gonilo trajnostnega razvoja posameznika, organizacij in družbe

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:DSAIPA/DS/0022/2018
Naslov:GADgET

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:DSAIPA/DS/0113/2019
Naslov:AICE

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