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A Review On Machine Learning Classification Techniques For Plant Disease Detection

A REVIEW ON MACHINE LEARNING CLASSIFICATION TECHNIQUES FOR PLANT DISEASE DETECTION

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  • TCREPY19_11
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A REVIEW ON MACHINE LEARNING CLASSIFICATION TECHNIQUES FOR PLANT DISEASE DETECTION

 A Review on Machine Learning Classification Techniques for Plant Disease Detection

Abstract:

  The world Agriculture plays an essential role because of the rapid growth of population and increased in demand for food. Therefore, it needs to increase in crop yield. One major effect on low crop yield is disease caused by bacteria, virus and fungus. It can be prevented by using plant diseases detection techniques. Machine learning methods can be used for diseases identification because it mainly apply on data themselves and gives priority to outcomes of certain task. This paper presents the stages of general plant diseases detection system and comparative study on machine learning classification techniques for plant disease detection. In this survey it observed that Convolution Neural Network gives high accuracy and detects more number of diseases of multiple crops. CNN classifier detects more number of diseases with high accuracy. In future, other classification techniques in machine learning like decision trees, Naive Bayes classifier may be used for disease detection in plants and in the sense of helping farmer an automatic detection of all types of diseases in crop

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