Precision agriculture classification using convolutional neural networks for paddy growth level

Abstract

Precision Agricultural is a key component of modern agricultural. Several researchers tried to use various machine learning models as precision agricultural classification and recognition model, but surprisingly merely few researchers use Deep learning models to solve precision agriculture problems like Paddy Classification, Plant Classification or Fruit Classification. In this research, Precision Agriculture Classification on Paddy Image Dataset was performed using Convolutional Neural Networks. Paddy should be catered well in order tomonitor time to harvest, time to watering, and other tasks. The result of classification, we obtained 82% overall accuracy.