ARTIFICIAL INTELLIGENCE BASED IMAGE PROCESSING IDENTIFICATION MODEL - Shemles, Fikiradis
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Sesame plant is the most important types of a plant under the categories of oil crop. Different literature shows that the manual and experimental diagnosis of plant disease the result prone to biased and time and cost consumed. An intelligent diagnosis of plant disease gives a great effort for agricultural industries related to productivity. In this study, an intelligent model that diagnosis sesame plant disease that uses an integration of image processing and machine learning is studied. The main objective of the proposed system is to classify the captured image either infected or healthy…mehr

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Produktbeschreibung
Sesame plant is the most important types of a plant under the categories of oil crop. Different literature shows that the manual and experimental diagnosis of plant disease the result prone to biased and time and cost consumed. An intelligent diagnosis of plant disease gives a great effort for agricultural industries related to productivity. In this study, an intelligent model that diagnosis sesame plant disease that uses an integration of image processing and machine learning is studied. The main objective of the proposed system is to classify the captured image either infected or healthy plant using extracted features. In this study, the difference between healthy and diseased sesame plants was considered and investigating four types of disease these are Powdery Mildew, Bacterial blight, Cercospora leaf spot and Alternaria leaf spot with a total of five classes including healthy leaf.
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Autorenporträt
My name is Fikiradis Shemles I graduated with my first degree in Information Systems five years ago and immediately work for an assistant lecturer at Mekelle University, Ethiopia. I graduated with my second degree(MSc)from Mekelle university in computer science two years ago and am still working as a lecturer in Mekelle Univerisity.