Faster R-CNN Based Rice Leaf Disease Detection method

Resumen

Agriculture has a critical part in the country's economic development; hence it is critical to
ensure its advancement.Rice is prime meals of more than 65% of the Indians as it is the key
grain of India. The reach of varied diseases in rice plant has increased from past some decades.
There's a diversity of pathogens such as Bacterial, Fungal, Viral and they can damages the plant
parts like leafs from above and the bottom side. The factors like light, water, temperature,
radiation, atmosphere, humidity, acidity of soil and water affects the natural growth of
plants. It's observed that, the Rice plant’s diseases are the main contributors in the reduction of
production and quality of food. Recognition of such diseases may improve Production. These
crop diseases are creating troubles for farmers for low output and economic loss and agriculture
industry. So, it's need of ours to detect these diseases as early as possible. However, image
processing backgrounds hinder the diagnosis of rice plant illnesses. A new study could use
Faster-RCNN to identify rice leaf disease. To diagnose rice leaf diseases, Ipresent a Faster-
RCNN based model.I use here a novel dataset of field data and Kaggle dataset for rice leaf
disease images.