SegFormer-based nectar source segmentation in remote sensing imagery.

ABSTRACT:

Introduction

Beekeepers often face challenges in accurately determining the spatial distribution of nectar-producing plants, which is crucial for informed decision-making and efficient beekeeping.

Methods

In this study, we present an efficient approach for automatically identifying nectar-producing plants using remote sensing imagery. High-resolution satellite images were collected and preprocessed, and an improved segmentation model based on the SegFormer architecture was developed. The model integrates the CBAM attention mechanism, deep residual structures, and a spatial feature enhancement module to improve segmentation accuracy.

Results

Experimental results on rapeseed flower images from Wuyuan County demonstrate that the improved model outperforms the baseline Se

SUBMITTER: Dong M 

PROVIDER: S-EPMC12521987 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature