Análisis comparativo de clasificadores para gestos descritos por LaGeR

dc.contributor.advisor	Erick Mata Montero, Ph.D.	es
dc.contributor.author	Mesén-Solórzano, Milena María
dc.date.accessioned	2019-02-18T14:51:54Z
dc.date.available	2019-02-18T14:51:54Z
dc.date.issued	2018
dc.identifier.uri	https://hdl.handle.net/2238/10345
dc.description	Proyecto de Graduación (Maestría en Computación) Instituto Tecnológico de Costa Rica, Escuela de Ingeniería en Computación, 2018.	es
dc.description.abstract	The present thesis is a comparative analysis between the Damerau-Levenshtein algorithm and a deep learning algorithm and con rms that, by using deep learning techniques, one can obtain better results when recognizing gestures described by LaGeR, in terms of both running time and accuracy. Additionally, it shows that said method is e ective with several input devices. xvii	es
dc.language.iso	spa	es
dc.publisher	Instituto Tecnológico de Costa Rica	es
dc.rights	acceso abierto	es
dc.subject	Algoritmo Damerau- Levenshtein	es
dc.subject	Algoritmo de deep learning	es
dc.subject	LaGeR	es
dc.subject	Research Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer science	es
dc.title	Análisis comparativo de clasificadores para gestos descritos por LaGeR	es
dc.type	tesis de maestría	es