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Pest Prediction System using Machine Learning under Controlled Environment for Capsicum Crop

Suhas Labade, Omprakash Rajanakar

Abstract


Early identification and diagnosis of plant diseases is vital for the overall development of the agricultural sector in India. Farmer’s estimations and general observations are time consuming, sometimes vague and interpreting wrong evaluation. For this reason, a suitable deep neural network is proposed to automatically identify pepper disease which relates with climatic conditions. This classification includes 3 diseases and 2 healthy and unhealthy classifications. Experimentation carried out on a manually collected data samples of 1913 images. The estimation of network performance dependent on optimization. In this paper possible pest attacks dependent on climatic parameters which reviewed subjectively, and classification results on of image data based on Adam classifier given. 


Keywords


Capsicum disease, deep neural network, classification, test accuracy

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References


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