A Survey on The Machine Learning Techniques in Crop Disease Detection
Keywords:
Machine learning, crop disease, Random Forest test, Convolution Neural networks (CNN), Fuzzy LogicAbstract
Crop infections are a substantial danger to nourishment security, but their rapid identifying evidence continues problematic in many parts of the globe due to the non presence of the fundamental foundation. Crop infections are a substantial danger to nourishment security, but their rapid identifying evidence continues problematic in many parts of the globe because of the non presence of the fundamental foundation. Hence, machine learning methods such as Random Forest test, Convolution Neural networks (CNN), Fuzzy Logic etc., are utilized to identify illnesses in plant leaves since it examines the data from many aspects, as well as classifies it into one of the preset set of classes. The morphological traits and attributes like color, intensity or size of the plants are taken into account for categorization. This study offers an overview on several forms of plant illnesses and distinct classification algorithms in machine learning which are used for diagnosing diseases in various plants.
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