Pest-YOLO: A model for large-scale multi-class dense and tiny pest detection and counting.

ABSTRACT: Frequent outbreaks of agricultural pests can reduce crop production severely and restrict agricultural production. Therefore, automatic monitoring and precise recognition of crop pests have a high practical value in the process of agricultural planting. In recent years, pest recognition and detection have been rapidly improved with the development of deep learning-based methods. Although certain progress has been made in the research on pest detection and identification technology based on deep learning, there are still many problems in the production application in a field environment. This work presents a pest detector for multi-category dense and tiny pests named the Pest-YOLO. First, the idea of focal loss is introduced into the loss function using weight distribution to improve the at

SUBMITTER: Wen C 

PROVIDER: S-EPMC9783619 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature