Method for assessing rodent infestation in plateau based on SegFormer
Xiangjie Huang, Guoying Zhang, Chunmei Li, Yaosheng Han, Qing Dong, Hao Wang
TL;DR
This paper introduces a new method using the SegFormer model to detect rodent burrows in plateau areas, aiding grassland restoration and management.
Contribution
A modified SegFormer model, EM-SegFormer, is proposed to improve detection of small rodent burrows in complex environments.
Findings
EM-SegFormer outperforms standard SegFormer in detecting rodent burrows on the plateau.
The model incorporates EMA and MCFN to enhance global context and detail recovery.
The method provides reliable technical support for grassland restoration.
Abstract
Rodent infestation is a critical factor contributing to grassland degradation, which significantly negatively affects grassland ecosystems. To assess rodent infestation on the plateau, there is an urgent need for a scientifically sound and effective method to detect the distribution of rodent burrows. In response, this study proposes a semantic segmentation approach utilizing the SegFormer model to detect rodent infestation in highland areas. First, we used an unmanned aerial vehicle to collect video data from the plateau and constructed a rodent burrows dataset after processing and precise labeling. Second, to address the issue of SegFormer’s suboptimal performance in segmenting small targets within complex backgrounds and among similar objects, we implemented targeted modifications to enhance its effectiveness for this task. Incorporating the efficient multi-scale attention (EMA)…
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Taxonomy
TopicsYersinia bacterium, plague, ectoparasites research · Wildlife Ecology and Conservation · Species Distribution and Climate Change