Using Artificial Neural Networks for Detecting Damage on Tobacco Leaves Caused by Blue Mold
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 8
Abstract
Worldwide, the monitoring of pests and diseases plays a fundamental role in the agricultural sustainability; making necessary the development of new tools for early pest detection. In this sense, we present a software application for detecting damage in tobacco (Nicotiana tabacum L.) leaves caused by the fungus of blue mold (Peronospora tabacina Adam). This software application processes tobacco leaves images using a pat-tern recognition technique known as Artificial Neural Network. For the training and testing stages, a total of 40 images of tobacco leaves were used. The experimentation carried out shows that the developed model has accuracy higher than 97% and there is no significant difference with a visual analysis carried out by experts in tobacco crop.
Authors and Affiliations
Himer Avila- George, Topacio Valdez- Morones, Humberto P´erez- Espinosa, Brenda Acevedo- Ju´arez, Wilson Castro
Keywords
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- EP ID EP376621
- DOI 10.14569/IJACSA.2018.090873
- Views 86
- Downloads 0
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