Classification of tomato leaf diseases using MobileNet v2

Tomato is a red-colored edible fruit originated from the American continent. There are a lot of plant diseases associated with tomatoes such as leaf mold, late blight, and mosaic virus. Tomato is an important vegetable crop that contributes to the world economically. Despite tremendous efforts in pl...

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Vydáno v:IAES International Journal of Artificial Intelligence Ročník 9; číslo 2; s. 290
Hlavní autoři: Zaki, Siti Zulaikha Muhammad, Asyraf Zulkifley, Mohd, Mohd Stofa, Marzuraikah, Kamari, Nor Azwan Mohammed, Ayuni Mohamed, Nur
Médium: Journal Article
Jazyk:angličtina
Vydáno: Yogyakarta IAES Institute of Advanced Engineering and Science 01.06.2020
Témata:
Algorithms
Blight
Computer vision
Deep learning
Image detection
Leaf mold
Machine learning
Medical imaging
Plant diseases
Plant management
Tomatoes
Viral diseases
Viruses
ISSN:2089-4872, 2252-8938, 2089-4872
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Abstract Tomato is a red-colored edible fruit originated from the American continent. There are a lot of plant diseases associated with tomatoes such as leaf mold, late blight, and mosaic virus. Tomato is an important vegetable crop that contributes to the world economically. Despite tremendous efforts in plant management, viral diseases are notoriously difficult to control and eradicate completely. Thus, accurate and faster detection of plant diseases is needed to mitigate the problem at the early stage. A computer vision approach is proposed to identify the disease by capturing the leaf images and detect the possibility of the diseases. A deep learning classifier is utilized to make a robust decision that covers a wide variety of leaf appearances. Compact deep learning architecture, which is MobileNet V2 has been fine-tuned to detect three types of tomato diseases. The algorithm is tested on 4,671 images from PlantVillage dataset. The results show that MobileNet V2 is able to detect the disease up to more than 90% accuracy.
AbstractList Tomato is a red-colored edible fruit originated from the American continent. There are a lot of plant diseases associated with tomatoes such as leaf mold, late blight, and mosaic virus. Tomato is an important vegetable crop that contributes to the world economically. Despite tremendous efforts in plant management, viral diseases are notoriously difficult to control and eradicate completely. Thus, accurate and faster detection of plant diseases is needed to mitigate the problem at the early stage. A computer vision approach is proposed to identify the disease by capturing the leaf images and detect the possibility of the diseases. A deep learning classifier is utilized to make a robust decision that covers a wide variety of leaf appearances. Compact deep learning architecture, which is MobileNet V2 has been fine-tuned to detect three types of tomato diseases. The algorithm is tested on 4,671 images from PlantVillage dataset. The results show that MobileNet V2 is able to detect the disease up to more than 90% accuracy.
Author Kamari, Nor Azwan Mohammed
Zaki, Siti Zulaikha Muhammad
Mohd Stofa, Marzuraikah
Asyraf Zulkifley, Mohd
Ayuni Mohamed, Nur
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Snippet Tomato is a red-colored edible fruit originated from the American continent. There are a lot of plant diseases associated with tomatoes such as leaf mold, late...
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StartPage 290
SubjectTerms Algorithms
Blight
Computer vision
Deep learning
Image detection
Leaf mold
Machine learning
Medical imaging
Plant diseases
Plant management
Tomatoes
Viral diseases
Viruses
Title Classification of tomato leaf diseases using MobileNet v2
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