Journal
COMPUTERS AND ELECTRONICS IN AGRICULTURE
Volume 178, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.compag.2020.105701
Keywords
Greenhouse tomato; Severity estimation; Disease detection; Machine learning
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The management of plant disease is a significant economic and environmental factor in the production of greenhouse tomato plants. Human expertise for assessing the presence and extent of disease is important in creating and implementing management plans, but it is difficult and expensive to acquire. In this paper, we present a new computer vision system to automatically recognize several diseases, detect previously unseen disease and to estimate per-leaf severity. Training and testing of models used several modified versions of the nine types of tomato disease of the PlantVillage tomato dataset and showed how different leaf properties impact disease detection.
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