PlantCaFo: An efficient few-shot plant disease recognition method based on foundation models.

ABSTRACT: Although plant disease recognition is highly important in agricultural production, traditional methods face challenges due to the high costs associated with data collection and the scarcity of samples. Few-shot plant disease identification tasks, which are based on transfer learning, can learn feature representations from a small amount of data; however, most of these methods require pretraining within the relevant domain. Recently, foundation models have demonstrated excellent performance in zero-shot and few-shot learning scenarios. In this study, we explore the potential of foundation models in plant disease recognition by proposing an efficient few-shot plant disease recognition model (PlantCaFo) based on foundation models. This model operates on an end-to-end network structure, integr

SUBMITTER: Jiang X 

PROVIDER: S-EPMC12709961 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature