Crop Disease Detection

Author(s)	SATHISHKUMAR S, POORNAVALLI P R, RITHIK P, JAHINA J
Country	India
Abstract	Detecting diseases in crops is a vital yet labor-intensive task in agriculture, often demanding extensive time and expert knowledge. This paper presents an innovative approach to crop disease detection using advanced computer vision and machine learning techniques. By automating the identification of common crop diseases, this system aims to reduce the reliance on expert intervention, expedite the diagnosis process, and ultimately improve crop management efficiency. The proposed method integrates deep learning models trained on a diverse dataset of diseased and healthy crop images, achieving high accuracy in disease recognition. This approach not only saves time but also provides farmers with a powerful tool to protect their crops from potential threats, thereby contributing to increased agricultural productivity and sustainability.
Keywords	Crop Disease Detection, Computer Vision, Machine Learning, Deep Learning, Agriculture, Automated Diagnosis, Precision Agriculture, Crop Management, Image Classification, Smart Farming.
Field	Engineering
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-11-15
Cite This	Crop Disease Detection - SATHISHKUMAR S, POORNAVALLI P R, RITHIK P, JAHINA J - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30399
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.30399
Short DOI	https://doi.org/g8rd4w

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