Computer vision in agriculture: APIs for detection and recognition of plant diseases
DOI:
https://doi.org/10.23925/1984-3585.2019i20p96-112Keywords:
Machine learning, Digital agriculture, Digital imaging, API, Computer visionAbstract
Artificial intelligence (AI) technology has made it possible to identify plant leaf diseases more accurately through image analysis, with beneficial effects to agriculture (cost, efficiency, quality). The article presents the results of studies using three distinct technologies (platforms) applied to one set of 50 images of four plant diseases, showing the visual characteristics of each of them. The study was divided into two stages. The first was carried out with 30 images and the second with 20. The learning progress and the validation analysis were carried out by means of 10 frames. The purpose of testing was to compare disease recognition assertiveness on each technology / platform. Images of the following plant diseases were investigated in this study: Peronospora (downy mildew), Diplocarpon rosae (black spot), powdery mildew and Citrus Canker. The results of the identification of the diseases through images were positive.
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