GrapeScan - Grape Leaf Disease Detection
Abstract
Crop yield and quality of grapes are affected adversely by grapevine diseases. Manual inspection of grapes for health and diseases is inefficient due to high volume and potentially high error rates. The authors developed a system called GrapeScan using deep learning algorithms to classify photos of grape leaves into diseased or healthy categories. The system is based on a Convolutional Neural Network (CNN) trained on a publicly available dataset of grape leaves and is available for use in real-time via a web interface. The authors report results indicating that their system has high classification accuracy and low inference time, making it appropriate for use in precision agriculture and other practical farming applications.
Fields of Study & Subjects
Smart Agriculture and AI
Advanced Neural Network Applications
Industrial Vision Systems and Defect Detection
Publication details
- Journal / source
- International Journal on Advanced Computer Theory and Engineering
- Volume
- 15
- Issue
- 1S
- Pages
- 138–145
- Publication date
- 18 January 2026
- Language
- EN