A Deep Learning Framework for Automatic Disease Prediction towards Precision Farming

Authors : Siva Prasad Patnayakuni

Volume/Issue : Volume 8 - 2023, Issue 9 - September

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/ez9a2u8r

DOI : https://doi.org/10.5281/zenodo.8389177

Precision farming is technology-driven agriculture which is meant for improving performance in agricultural activities. With the emergence of Artificial Intelligence (AI), deep learning models are used for solving problems in different domains, particularly in computer vision applications. In this paper, we proposed an intelligent framework known as Deep Learning Framework for Precision Farming (DLF- PF). This framework exploits deep learning approach known as Convolutional Neural Network with enhanced layers for automatic detection of crop diseases. We proposed an algorithm known as Learning based Plant Disease Detection (LbPDD). This algorithm is designed to support CNN based supervised learning for detection of crop diseases. PlantVillege is the dataset used for empirical study in this paper. Our empirical study has revealed that the proposed model showed better performance over existing methods. Our framework is found suitable for usage in agricultural applications towards precision farming.

Keywords : Deep Learning, Agriculture, Smart Farming, Precision Farming, Artificial Intelligence.


Paper Submission Last Date
31 - December - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.