Publication Date: 2023/09/29
Abstract: 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.
DOI: https://doi.org/10.5281/zenodo.8389177
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23SEP815.pdf
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