A Novel Deep Learning Framework for Efficient Detection of Potato Leaf Diseases
Volume: 13 - Issue: 06 - Date: 01-06-2024
Approved ISSN: 2278-1412
Published Id: IJAECESTU407 | Page No.: 150-154
Author: Vikash Kumar
Co- Author: Swati Khanve,Dr .Sneha Soni
Abstract:-This paper timely and accurate detection of crop diseases is crucial for maintaining crop health and ensuring
optimal yield. This study proposes an innovative framework for detecting potato leaf disease by leveraging an efficient
deep learning model. The framework integrates advanced machine learning techniques to analyze and classify images of
potato leaves, identifying the presence of disease with high precision. The deep learning model employed demonstrates
superior efficiency in capturing intricate patterns and features associated with various stages of potato leaf diseases. The
proposed framework aims to provide a reliable and automated solution for farmers and agricultural practitioners,
enabling them to make prompt and informed decisions to manage and mitigate the impact of diseases on potato crops.
The utilization of cutting-edge technology in agricultural disease detection holds promise for enhancing overall crop
management practices and contributing to global food security
Key Words:-Potato leaf disease, Crop health, Disease detection, Deep learning model, Agricultural innovation, Image analysis, Machine learning, Agricultural technology
Area:-Engineering
DOI Member: 36.55.409
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