Clasificación de Especies : Un Enfoque para Mejorar la Precisión en la Identificación de Serpientes

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.

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Publication Details

Journal
Comunicaciones en Estadística
Published
2025-02-23
DOI
https://doi.org/10.15332/23393076.10770
Primary Topic
Educational Research and Science Teaching
Type
article
Field-Weighted Citation Impact
0.00
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article

Clasificación de Especies : Un Enfoque para Mejorar la Precisión en la Identificación de Serpientes

Osnamir Elías Bru Cordero, Díaz Sandoval, Cristian Téllez
Comunicaciones en Estadística
Educational Research and Science Teaching
article

Clasificación de Especies : Un Enfoque para Mejorar la Precisión en la Identificación de Serpientes

Osnamir Elías Bru Cordero, Díaz Sandoval, Cristian Téllez
article en

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.

Comunicaciones en EstadísticaVol. 17(2)
Openalex Percentile: Top 93%
Educational Research and Science Teaching
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Clasificación de Especies : Un Enfoque para Mejorar la Precisión en la Identificación de Serpientes — Osnamir Elías Bru Cordero, Díaz Sandoval, et al. · Comunicaciones en Estadística (2025) | TGRS Research Map | TGRS