Early recognition of tomato gray leaf spot disease based on MobileNetv2-YOLOv3 model.

Plant Methods
Jun Liu, Xuewei Wang

Abstract

Tomato gray leaf spot is a worldwide disease, especially in warm and humid areas. The continuous expansion of greenhouse tomato cultivation area and the frequent introduction of foreign varieties in recent years have increased the severity of the epidemic hazards of this disease in some tomato planting bases annually. This disease is a newly developed one. Thus, farmers generally lack prevention and control experience and measures in production; the disease is often misdiagnosed or not prevented and controlled timely; this condition results in tomato production reduction or crop failure, which causes severe economic losses to farmers. Therefore, tomato gray leaf spot disease should be identified in the early stage, which will be important in avoiding or reducing the economic loss caused by the disease. The advent of the era of big data has facilitated the use of machine learning method in disease identification. Therefore, deep learning method is proposed to realise the early recognition of tomato gray leaf spot. Tomato growers need to develop the app of image detection mobile terminal of tomato gray leaf spot disease to realise real-time detection of this disease. This study proposes an early recognition method of tomato leaf ...Continue Reading

References

Jun 14, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Shaoqing RenJian Sun
Oct 8, 2016·Frontiers in Plant Science·Sharada P MohantyMarcel Salathé
Dec 5, 2019·Frontiers in Plant Science·Alvaro FuentesDong Sun Park

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Methods Mentioned

BETA
feature extraction

Software Mentioned

YOLOv2
GoogleNet
MobileNet
YOLO
Faster
SqueezeNet
LeNet
MobileNetv2
YOLOv3
DenseNets

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