Plant disease recognition in a low data scenario using few-shot learning

Masoud Rezaei, Dean Diepeveen, Hamid Laga, Michael G. K. Jones, Ferdous Sohel

Abstract: Highlights•A few-shot learning approach is proposed for detecting plant diseases from images.•High performance was achieved using only a few training images per disease.•Vision transformers further improve performance, especially on complex samples.•Our proposed attention module reduces the impact of complicated backgrounds.•The high throughput and performance indicate its potential in precision farming.