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 | Multiple Crop Leaf Disease Detection and Classification Using Deep Learning |
|---|---|
| ABSTRACT | Crop diseases have a major negative impact on global food security and agricultural output. Effective crop management and economic loss control rely on the accurate and timely identification of plants illnesses. Traditional methods for identifying diseases, which are typically resource-intensive, subjective, and unfeasible for wide coverage, mostly rely on the human inspection of agricultural experts. In this research, we introduce an approach based on Deep learning (DL) framework for that identification and categorization of different crop leaf diseases. In order to automatically excerpt discriminating, include from the leaf photos and classify them into classes of healthy or unhealthy in various crop species, it uses a CNN, or Convolutional Neural Network architecture. The proposed approach combines feature extraction, data enrichment, picture pre-processing and model training to improve classification performance and generalization. According to the experimental findings, developed model demonstrate a remarkable performance with classification accuracy is 93.80 % in multi-crop data sets, proving its potential to detect Apple, Tomato, Potato, Grapes and Sugarcane leaf diseases efficiently. Moreover, the proposed model possesses excellent generalization ability, rendering it applicable for practical scenarios. It may help farmers detect crop diseases at an early stage. |
| AUTHOR | PURVA DHONDE, DAKSHA CHAUDHARI, SANIKA LOKHANDE, SWAPNIL BANGAL UG Student, Dept. of Electronic & Computer Engineering, PREC, Loni, Maharashtra, India Assistant Professor, Dept. of Electronic &Computer Engineering, PREC, Loni, Maharashtra, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405110 |
| pdf/110_Multiple Crop Leaf Disease Detection and Classification Using Deep Learning.pdf | |
| KEYWORDS | |
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