Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM35352
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Plant diseases significantly threaten global food security, resulting in substantial agricultural losses annually. Early detection and accurate classification of plant diseases can help farmers take timely preventive measures, thereby mitigating crop damage and improving yield. This research aims to develop a machine learning-based model on top of EfficientNetB3 for detecting and classifying plant diseases from leaf images. The proposed model has achieved 99.4% testing accuracy. This study is focused on a deep learning model to detect disease in plant leaves. But, in the future model can be integrated with a drone or any other system to detect diseases from plants and report the diseased plant’s location to people so that they can be cured accordingly.
KEYWORDS
Publication Date
4/10/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...