ABSTRACT
India is one of the largest producers of rice. About 3.5 billion people use rice as a food staple around the world. In India, rice is cultivated in all regions. About 60% of the food contribution is in the form of rice. The average production of rice during the year 2020–2021 was 121.46 million tons which is an increase by 9.01 million tons when compared to the previous year. Even though the production is high, farmers are still facing huge economic losses. Insects are causing more damage at all stages of rice cultivation and affect up to 30% of crop production loss. Insects that cause production losses are leafhoppers, borers, gall midge, plant hoppers, and grainsucking bugs. Identification of these pests at an early stage is a major concern for all farmers. Early identification can reduce damage and production loss. Convolutional neural networks (CNN) are mostly employed for image classification. Throughout this framework, we categorized pests that affect rice production using the one, three, and four-layer convolutional neural networks as well as the VGG19 deep transfer learning model.
Paddy crop, Pest attacks, Leaf disease, Deep learning model; CNN, VGG19
