Volume 11, Issue 1, 2018, Pages 86 - 100
Evaluation of Expert Systems Techniques for Classifying Different Stages of Coffee Rust Infection in Hyperspectral Images
Authors
Wilson Castro1, wilson.castro@upn.edu.pe, Jimy Oblitas2, j_oblitas@hotmail.com, Jorge Maicelo3, jmaicelo@indes-ces.edu.pe, Himer Avila-George4, himerag@cicese.mx
1Facultad de Ingeniería, Universidad Privada del Norte, Cajamarca, Cajamarca 06002, Perú.
2Centro de Investigaciones e Innovaciones de la Agroindustria Peruana (CIIAP), Amazonas, 1061, Perú.
3Facultad de Ingeniería Zootecnista, Agronegocios y Biotecnología, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas, Chachapoyas, Chachapoyas 01001, Perú.
4Unidad de Transferencia Tecnológica Tepic, CONACYT-CICESE, Tepic, Nayarit 63173, México.
Received 30 November 2016, Accepted 17 September 2017, Available Online 1 January 2018.
- DOI
- 10.2991/ijcis.11.1.8How to use a DOI?
- Keywords
- Expert systems; Hyperspectral images; Coffee rust infection; Spectral profiles
- Abstract
In this work, the use of expert systems and hyperspectral imaging in the determination of coffee rust infection was evaluated. Three classifiers were trained using spectral profiles from different stages of infection, and the classifier based on a support vector machine provided the best performance. When this classifier was compared to visual analysis, statistically significant differences were observed, and the highest sensitivity of the selected classifier was found at early stages of infection.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Wilson Castro AU - Jimy Oblitas AU - Jorge Maicelo AU - Himer Avila-George PY - 2018 DA - 2018/01/01 TI - Evaluation of Expert Systems Techniques for Classifying Different Stages of Coffee Rust Infection in Hyperspectral Images JO - International Journal of Computational Intelligence Systems SP - 86 EP - 100 VL - 11 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.11.1.8 DO - 10.2991/ijcis.11.1.8 ID - Castro2018 ER -