Edge AI and Computer Vision for Real-Time Foliar Crop Disease Detection on Resource-Constrained Mobile Devices
Deployment of quantized MobileNet models on low-cost smartphones enabling offline diagnosis of maize lethal necrosis, potato late blight, and cassava mosaic disease with 94.2% top-1 accuracy.
- Year
- 2025
- Published
- 25 Jun 2025
- Published in
- ACM Conference on Computing and Sustainable Societies (COMPASS 2025)