Semi-supervised few-shot learning approach for plant diseases recognition

• Published in: Plant methods Vol. 17; no. 1; p. 68
• Main Authors: Li, Yang, Chao, Xuewei
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 27.06.2021; BioMed Central; BMC
• Subjects: Agricultural production; Agriculture; Classification; confidence interval; Confidence intervals; data collection; Datasets; Deep learning; Diagnosis; domain; Domains; Labeling; Learning; Leaves; Machine learning; Plant diseases; Plants; Recognition; Self-adaption; Semi-supervised learning; Supervised learning; Transfer learning; Unmanned aerial vehicles; China

Learning from a few samples to automatically recognize the plant leaf diseases is an attractive and promising study to protect the agricultural yield and quality. The existing few-shot classification studies in agriculture are mainly based on supervised learning schemes, ignoring unlabeled data'...