Análisis comparativo de clasificadores para gestos descritos por LaGeR

dc.contributorErick Mata Montero, Ph.D.
dc.creatorMesén-Solórzano, Milena María
dc.date.accessioned2019-02-18T14:51:54Z
dc.date.accessioned2022-10-19T22:53:37Z
dc.date.available2019-02-18T14:51:54Z
dc.date.available2022-10-19T22:53:37Z
dc.date.created2019-02-18T14:51:54Z
dc.date.issued2018
dc.identifierhttps://hdl.handle.net/2238/10345
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4512858
dc.description.abstractThe 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
dc.languagespa
dc.publisherInstituto Tecnológico de Costa Rica
dc.subjectAlgoritmo Damerau- Levenshtein
dc.subjectAlgoritmo de deep learning
dc.subjectLaGeR
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer science
dc.titleAnálisis comparativo de clasificadores para gestos descritos por LaGeR
dc.typeinfo:eu-repo/semantics/masterThesis


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