Akses Terbuka DOI: 10.5555/fji-demo-005 Cara menggunakan DOI?
Federated Learning for Crop Disease Detection Without Sharing Farm Data
Rina Kusuma* iD1, Hendra Wijaya2
Abstrak
⇩ Unduh PDF
Farmers are reluctant to share crop imagery due to privacy concerns. We train a federated disease-detection model across 40 farms without centralizing images. The federated model reaches 91.4% accuracy, within 1.2 points of a centralized baseline, demonstrating that privacy-preserving training is viable for agricultural AI.
Kata kunci: federated learning; agriculture; privacy; computer vision
Sitasi artikel ini
Rina Kusuma, Hendra Wijaya (2026). Federated Learning for Crop Disease Detection Without Sharing Farm Data. Sustainable Technology Proceedings, 2, 9–16. https://doi.org/10.5555/fji-demo-005
- DOI
- 10.5555/fji-demo-005
- Tipe artikel
- Studi Kasus
- Halaman
- 9–16
- Terbit
- 2026-06-15
- Metrik
- 243 dilihat · 99 diunduh