Computer Vision-Based Ovitrap for Dengue Control-Reference-Cited by-同舟云学术

Computer Vision-Based Ovitrap for Dengue Control

Published:2022 Issue: Volume: Page:123-135
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Abad-Salinas Jesús Emmanuel^ORCID,Montero-Valverde José Antonio^ORCID,Hernández-Hernández José Luis^ORCID,Cruz-Guzmán Virgilio^ORCID,Martínez-Arroyo Miriam^ORCID,de la Cruz-Gámez Eduardo^ORCID,Hernández-Hernández Mario^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-19961-5_9

Reference19 articles.

1. Santos, D.A., Rodrigues, J.J., Furtado, V., Saleem, K., Korotaev, V.: Automated electronic approaches for detecting disease vectors mosquitoes through the wing-beat frequency. J. Cleaner Prod. 217, 767–775 (2019). https://doi.org/10.1016/j.jclepro.2019.01.187

2. Guzmán, V.C., Pelta, D.A., Verdegay, J.L.: Fuzzy maximal covering location models for fighting dengue. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–7, Dec, IEEE. https://doi.org/10.1109/SSCI.2016.7850139

3. CENAPRECE (Centro Nacional de Programas Preventivos y Control de Enfermedades): Guía metodológica para la vigilancia entomológica con ovitrampas (2015)

4. Quimbayo, M., Rúa-Uribe, G., Parra-Henao, G., Torres, C.: Evaluación de ovitrampas letales como estrategia para el control de Aedes aegypti. Biomedica 34(3), 473–482 (2014). https://doi.org/10.7705/biomedica.v34i3.2146

5. Balladares Orellana, M.P.: Diseño de ovitrampa para el diagnóstico y control de vectores Aedes aegypti. Caso de estudio Instituto Nacional de Investigación en Salud Pública (2018)