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
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.
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.
