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Intelligent Leaf Disease Classification using Machine Learning Technique


Affiliations
1 Quebec Centre for Biodiversity Science (QCBS), Montreal, QC, Canada
2 Vision and Imagery Team, Computer Research Institute of Montréal, Montréal, QC, Canada
     

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Agriculture is the major occupation and plays a key function in India. The rural people rely upon on agriculture as their major livelihood. In the plant growing stage, there are typically contaminated with extraordinary diseases. The farmers have ability to perceive the ailment in the early stage and take precautions. But it is impossible to become aware of the ailment caused with the aid of the crop with naked eye. A novel way of training and methodology was used to expedite a quick and easy implementation of the system in practice. The developed model was able to recognise various types of tea leaf disease sout of healthy leaves.


Keywords

Tea Leaf Diseases Classification, Machine Learning Classification.
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  • Intelligent Leaf Disease Classification using Machine Learning Technique

Abstract Views: 224  |  PDF Views: 1

Authors

Serawork Wallelign
Quebec Centre for Biodiversity Science (QCBS), Montreal, QC, Canada
Fumio Okura
Vision and Imagery Team, Computer Research Institute of Montréal, Montréal, QC, Canada

Abstract


Agriculture is the major occupation and plays a key function in India. The rural people rely upon on agriculture as their major livelihood. In the plant growing stage, there are typically contaminated with extraordinary diseases. The farmers have ability to perceive the ailment in the early stage and take precautions. But it is impossible to become aware of the ailment caused with the aid of the crop with naked eye. A novel way of training and methodology was used to expedite a quick and easy implementation of the system in practice. The developed model was able to recognise various types of tea leaf disease sout of healthy leaves.


Keywords


Tea Leaf Diseases Classification, Machine Learning Classification.