MSCF-LUNet: a lightweight three-stage pine wilt disease segmentation model with multi-scale context fusion mechanism.

ABSTRACT:

Introduction

Pine wilt disease (PWD) is a highly destructive infectious disease that severely damages pine forests worldwide. Because symptoms emerge first in the tree crown, detection from unmanned aerial vehicles (UAVs) is efficient. However, most methods perform only binary classification and lack pixel-level staging, which leads to missed initial symptoms and confusion with other species.

Methods

We propose MSCF-LUNet, a lightweight three-stage semantic segmentation model based on multi-scale context fusion. The model uses an improved multi-scale patch embedding guided by attention with relative position encoding (AWRP) to adapt the sampling field of view and to fuse local details with global context. Under contextual attention, the network learns fine-grained features a

SUBMITTER: Zhou D 

PROVIDER: S-EPMC12835376 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature