International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | LeafNet: A Robust Deep Learning Framework for Early Plant Disease Detection and Smart Remedy Recommendation |
|---|---|
| ABSTRACT | Agriculture plays a vital role in the economic development of many countries, and plant diseases significantly affect crop productivity and farmers’ livelihoods. Traditional disease detection methods are often time-consuming, inaccurate, and require expert supervision. With the advancement of artificial intelligence, deep learning techniques have emerged as efficient solutions for automated disease detection. This paper presents a plant disease detection system using Convolutional Neural Networks (CNNs) to identify diseases from plant leaf images. The proposed system processes leaf images through preprocessing stages such as resizing and normalization before feeding them into a CNN model for classification. The trained model predicts whether a leaf is healthy or infected and provides suitable remedies or pesticide recommendations. Experimental results show that the model achieves high accuracy in disease classification, making it a practical and efficient solution for real-time agricultural disease monitoring. This system contributes to precision agriculture by enabling timely disease detection, reducing crop loss, and improving farming sustainability. |
| AUTHOR | JOSEPH AMBROSE, KEERTHANA N M, KIRANMAYI H K, MANGALAGOURI V G, PROF. ARCHANA K N UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404075 |
| pdf/75_LeafNet A Robust Deep Learning Framework for Early Plant Disease Detection and Smart Remedy Recommendation.pdf | |
| KEYWORDS | |
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