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 | AI-Powered Grape Detection and Disease Classification System |
|---|---|
| ABSTRACT | Grape cultivation underpins a global industry generating over USD 300 billion annually, yet fungal and oomycete diseases remain a persistent threat, causing yield losses of 20–40% per season in vulnerable viticultural regions. Timely and accurate identification of foliar and fruit disorders is critical to sustainable crop management. This paper proposes an end-to-end deep learning system for fine-grained disease classification across seven categories—Black Rot, Downy Mildew, Powdery Mildew, Leaf Blight (Isariopsis Leaf Spot), Esca (Black Measles), Gray Mold (Botrytis Bunch Rot), and Healthy—using a transfer-learned EfficientNet-B3 backbone trained on a curated Kaggle grape disease dataset of over 14,000 augmented images. A two-stage fine-tuning strategy and a domain-adapted augmentation pipeline are employed to maximise generalisation under realistic field imaging conditions. The proposed system achieves an overall top-1 classification accuracy of 96.4%, a macro-averaged F1-score of 0.963, and a mean GPU inference latency of 38 ms. Comparative experiments with VGG-16, ResNet-50, and MobileNetV2 confirm the superiority of the proposed approach, demonstrating that automated vision-based screening can serve as a practical, low-cost decision-support tool for vineyard disease management. |
| AUTHOR | SAHIL RAJENDRA DHAMALE, VEDANT VIJAY KANOJE, RITESH KASHINATH AUTI, TEJAS GANESH KHODKE, PROF. SONIYA WAGHMARE Department of Computer Engineering, JSPM’s Padmabhooshan Vasantdada Patil Institute of Technology, Pune, India Guide, JSPM’s Padmabhooshan Vasantdada Patil Institute of Technology, Pune, India |
| VOLUME | 185 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1406026 |
| pdf/26_AI-Powered Grape Detection and Disease Classification System.pdf | |
| KEYWORDS | |
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