Abstract:
With increase productivity and profit
margins, it is imperative to control economic and
yield losses of agricultural produce. Manual monitoring of crops is becoming challenging year after
year and isn’t scalable for large scale cultivation.
Hence, in this paper, we discuss various methods
used or researched to detect crop diseases in Rice
plant using traditional image processing techniques
and neural networks. This paper explores possibility of using semantic segmentation to extract the
affected area and calculating the affected area and
estimate the severity. For easier usage, the model is
deployed using ngrok and Twilio server to accept,
process and return output on WhatsApp interface.
