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  2. Volume 8, Issue 2
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Online ISSN: 2515-8260

Volume8, Issue2

Digital Image Processing Techniques For Detecting And Classifying Plant Diseases

    Anandita Mishra Dr.Raju Barskar Prof. Uday chourasia

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 2, Pages 545-550

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Abstract

One of the biggest revolutions of modern history is the invention of agriculture for a healthier lifestyle. It significantly changed the human culture and played an important role in the development of the population and biological improvements in food production and domestication. Study into agriculture is then planned by improving the disease diagnostics method with the use of newer information technology to enhance efficiency and quantity for agricultural production and its allied operation. This project focuses on the identification and diagnosis of plant leaf diseases of tomatoes and pomegranate based on visual symptoms, anthracnose, and powdery mildew. Machine learning and image processing using SVM, KNN require many steps to identify and distinguish disease signs
Keywords:
    Machine learning Image processing plant disease SVM
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(2021). Digital Image Processing Techniques For Detecting And Classifying Plant Diseases. European Journal of Molecular & Clinical Medicine, 8(2), 545-550.
Anandita Mishra; Dr.Raju Barskar; Prof. Uday chourasia. "Digital Image Processing Techniques For Detecting And Classifying Plant Diseases". European Journal of Molecular & Clinical Medicine, 8, 2, 2021, 545-550.
(2021). 'Digital Image Processing Techniques For Detecting And Classifying Plant Diseases', European Journal of Molecular & Clinical Medicine, 8(2), pp. 545-550.
Digital Image Processing Techniques For Detecting And Classifying Plant Diseases. European Journal of Molecular & Clinical Medicine, 2021; 8(2): 545-550.
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