Identification of leaves of wild Ussurian Pear (<i>Pyrus ussuriensis</i>) based on YOLOv10n-MCS.

ABSTRACT:

Introduction

Wild Ussurian Pear germplasm resource has rich genetic diversity, which is the basis for genetic improvement of pear varieties. Accurately and efficiently identifying wild Ussurian Pear accession is a prerequisite for germplasm conservation and utilization.

Methods

We proposed YOLOv10n-MCS, an improved model featuring: (1) Mixed Local Channel Attention (MLCA) module for enhanced feature extraction, (2) Simplified Spatial Pyramid Pooling-Fast (SimSPPF) for multi-scale feature capture, and (3) C2f_SCConv backbone to reduce computational redundancy. The model was trained on a self-made dataset of 16,079 wild Ussurian Pear leaves images.

Results

Experiment results demonstrate that the precision, recall, mAP50, parameters, FLOPs, and model size of YOLOv10n-MCS

SUBMITTER: Li N 

PROVIDER: S-EPMC12267203 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature