Neural Network based Smart Weed Detection System

Agriculture is a critical field of economy that needs consistent care and attention. The crops during the growing phase regularly need tending and are prone to pest and weed infestation that severely affects crop productivity. In today’s age when sufficient man power is not available in agriculture, machine learning and neural networks can be used to detect the weeds in the crop field. . It would also help in harvesting of species at different times to improve production and labor costs. The present paper attempts to demonstrate an automatic plant and weed identification system that could be extremely beneficial for application of pesticides, fertilizers and weedicides. The model developed in this paper employs a Convolutional neural network to extract image features and provide for early detection of weeds in crop field with better accuracy.