Method for the recovery of images in databases of skin cancer

Viloria, Amelec; Varela, Noel; Nuñez-Bravo, Narledys; Pineda Lezama, Omar Bonerge

doi:https://doi.org/10.1007/978-981-15-7234-0_94

dc.contributor.author	Viloria, Amelec	spa
dc.contributor.author	Varela, Noel	spa
dc.contributor.author	Nuñez-Bravo, Narledys	spa
dc.contributor.author	Pineda Lezama, Omar Bonerge	spa
dc.date.accessioned	2021-01-18T17:39:40Z
dc.date.available	2021-01-18T17:39:40Z
dc.date.issued	2021
dc.identifier.uri	https://hdl.handle.net/11323/7708	spa
dc.description.abstract	Deep learning is widely used for the classification of images since the ImageNet competition in 2012 (Zaharia et al. in Common ACM 59(11):56–65, 2016, [1]; Tajbakhsh et al. in IEEE Trans Med Imaging 35(5):1299–1312, 2016, [2]). This image classification is very useful in the field of medicine, in which there is a growing interest in the use of data mining techniques in recent years. In this paper, a deep learning network was selected and trained for the analysis of a set of skin cancer data, obtaining very satisfactory results, as the model surpassed the classification results of trained dermatologists using a dermatoscope, other automatic learning techniques, and other deep learning techniques.	spa
dc.format.mimetype	application/pdf	spa
dc.language.iso	eng
dc.publisher	Corporación Universidad de la Costa	spa
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International	spa
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	spa
dc.source	Advances in Intelligent Systems and Computing	spa
dc.subject	Deep learning	spa
dc.subject	Medical images	spa
dc.subject	Clinical data analysis	spa
dc.title	Method for the recovery of images in databases of skin cancer	spa
dc.type	Artículo de revista	spa
dc.source.url	https://link.springer.com/chapter/10.1007/978-981-15-7234-0_94	spa
dc.rights.accessrights	info:eu-repo/semantics/openAccess	spa
dc.identifier.doi	https://doi.org/10.1007/978-981-15-7234-0_94	spa
dc.identifier.instname	Corporación Universidad de la Costa	spa
dc.identifier.reponame	REDICUC - Repositorio CUC	spa
dc.identifier.repourl	https://repositorio.cuc.edu.co/	spa
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