Clasificación De Especies: Un Enfoque Para Mejorar La Precisión En La Identificación De Serpientes
dc.contributor.advisor | Bru Cordero, Osnamir | |
dc.contributor.author | Ruiz Sandoval, Diego Ferney | |
dc.contributor.corporatename | Universidad Santo Tomás | spa |
dc.contributor.cvlac | https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001425196 | spa |
dc.contributor.googlescholar | https://scholar.google.com/citations?user=jtoOoEIAAAAJ&hl=es&oi=ao | spa |
dc.contributor.orcid | https://orcid.org/0000-0001-9425-9475 | spa |
dc.coverage.campus | CRAI-USTA Bogotá | spa |
dc.date.accessioned | 2025-01-27T15:11:41Z | |
dc.date.available | 2025-01-27T15:11:41Z | |
dc.date.issued | 2024 | |
dc.description | Este trabajo tiene como objetivo aplicar técnicas modernas de análisis de datos, en particular redes neuronales, para mejorar la clasificación de especies de serpientes en Colombia, utilizando información obtenida de registros y observaciones compartidas en plataformas sociales como Facebook, donde los usuarios documentan avistamientos y características de las serpientes. Además de la clasificación precisa de las especies, se espera identificar patrones en la distribución geográfica y comportamientos de estas. Aunque las redes neuronales ofrecen una ventaja significativa en términos de precisión, presentan la desventaja de ser modelos de "caja negra", lo que dificulta su interpretación. A pesar de esta limitación, el estudio se basa en evidencia de investigaciones previas y en datos de la comunidad en línea, con la expectativa de mejorar tanto la identificación de especies como la comprensión de sus patrones de distribución, contribuyendo al desarrollo de estrategias de conservación más efectivas y a la protección de la biodiversidad en Colombia. | spa |
dc.description.abstract | This work aims to apply modern data analysis techniques, particularly neural networks, to improve the classification of snake species in Colombia, using information obtained from records and observations shared on social platforms like Facebook, where users document sightings and characteristics of snakes. In addition to the accurate classification of species, the study is expected to identify patterns in the geographical distribution and behaviors of these species. While neural networks offer a significant advantage in terms of accuracy, they have the disadvantage of being ”black box”models, making them difficult to interpret. Despite this limitation, the study builds on evidence from previous research and data from the online community, with the expectation of improving both species identification and understanding of distribution patterns, contributing to the development of more effective conservation strategies and the protection of biodiversity in Colombia. | spa |
dc.description.degreelevel | Maestría | spa |
dc.description.degreename | Magister en Estadística Aplicada | spa |
dc.format.mimetype | application/pdf | spa |
dc.identifier.citation | Ruiz Sandoval, D. F. (2024). Clasificación de especies: Un enfoque para mejorar la precisión en la identificación de serpientes. [Trabajo de Maestría, Universidad Santo Tomás].Repositorio institucional. | spa |
dc.identifier.instname | instname:Universidad Santo Tomás | spa |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad Santo Tomás | spa |
dc.identifier.repourl | repourl:https://repository.usta.edu.co | spa |
dc.identifier.uri | http://hdl.handle.net/11634/59505 | |
dc.language.iso | spa | spa |
dc.publisher | Universidad Santo Tomás | spa |
dc.publisher.faculty | Facultad de Estadística | spa |
dc.publisher.program | Maestría Estadística Aplicada | spa |
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dc.rights | Atribución-NoComercial-SinDerivadas 2.5 Colombia | * |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
dc.rights.local | Abierto (Texto Completo) | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | * |
dc.subject.keyword | Layers | spa |
dc.subject.keyword | Machine Learning | spa |
dc.subject.keyword | Neural Networks | spa |
dc.subject.keyword | Deep Learning | spa |
dc.subject.keyword | Probability | spa |
dc.subject.keyword | Classification | spa |
dc.subject.keyword | Perceptron | spa |
dc.subject.lemb | Estadística | spa |
dc.subject.lemb | Estadística Aplicada | spa |
dc.subject.lemb | Especie | spa |
dc.subject.proposal | Capas | spa |
dc.subject.proposal | Machine learning | spa |
dc.subject.proposal | Redes Neuronales | spa |
dc.subject.proposal | Deep Learning | spa |
dc.subject.proposal | Probabilidad | spa |
dc.subject.proposal | Clasificación | spa |
dc.subject.proposal | Perceptron | spa |
dc.title | Clasificación De Especies: Un Enfoque Para Mejorar La Precisión En La Identificación De Serpientes | spa |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
dc.type.drive | info:eu-repo/semantics/masterThesis | |
dc.type.local | Tesis de maestría | spa |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
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