Ontology highlight
ABSTRACT:
SUBMITTER: Niu Y
PROVIDER: S-EPMC10374091 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
Niu Yupeng Y Lu Ming M Liang Xinyun X Wu Qianqian Q Mu Jiong J
PloS one 20230727 7
Real-time, rapid, accurate, and non-destructive batch testing of fruit growth state is crucial for improving economic benefits. However, for plums, environmental variability, multi-scale, occlusion, overlapping of leaves or fruits pose significant challenges to accurate and complete labeling using mainstream algorithms like YOLOv5. In this study, we established the first artificial dataset of plums and used deep learning to improve target detection. Our improved YOLOv5 algorithm achieved more ac ...[more]