APPLICATIONS OF DEEP LEARNING IN AGRICULTURE (PEST-DETECTION)

Abstract

Due to increased global trade and demand for food products, agriculture has grown dramatically in recent years. The nation's economy is significantly impacted by this. As the second-largest producer of food in the world, agriculture plays a significant role in the Indian economy. The agricultural sector is one that could benefit from digital technologies. Additionally, it supports a number of small-scale industries by creating jobs. Deep learning approaches are used to improve performance across a wide range of industries. Deep learning is a component of machine learning. It has been used in many smart agriculture applications, including water and soil management, crop cultivation, crop disease detection, weed removal, crop distribution, robust fruit counting, and yield prediction. Pests are a type of arthropod that causes significant problems in agriculture. They have ruined a lot of food, costing farmers money all around and having a variety of negative effects on food production. The purpose of this paper is to discuss how to utilize deep learning in pest detection.