Transferring Face Recognition Techniques to Entomology: An ArcFace and ResNet Approach for Improving Dragonfly Classification
Source abstract
Abstract
Dragonfly classification is crucial for biodiversity conservation. Traditional taxonomic approaches require extensive training and experience, limiting their efficiency. Computer vision offers promising solutions for dragonfly taxonomy. In this study, we adapt the face recognition algorithms for the classification of dragonfly species, achieving efficient recognition of categories with extremely small differences between classes. Meanwhile, this method can also reclassify data that were incorrectly labeled. The model is mainly built based on the classic face recognition algorithm (ResNet50+ArcFace), and ResNet50 is used as the comparison algorithm for model performance. Three datasets with different inter-class data distributions were constructed based on two dragonfly image data sources: Data1, Data2 and Data3. Ultimately, our model achieved Top1 accuracy rates of 94.3%, 85.7%, and 90.2% on the three datasets, surpassing ResNet50 by 0.6, 1.5, and 1.6 percentage points, respectively. Under the confidence thresholds of 0.7, 0.8, 0.9, and 0.95, the Top1 accuracy rates on the three datasets were 96.0%, 97.4%, 98.7%, and 99.2%, respectively. In conclusion, our research provides a novel approach for species classification. Furthermore, it can calculate the similarity between classes while predicting categories, thereby offering the potential to provide technical support for biological research on the similarity between species.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Orthoptera Research and Taxonomy · Species Distribution and Climate Change · Fossil Insects in Amber
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
Biodiversity Data Center of Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
Yunnan Key Laboratory of Biodiversity Information, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
Kunming Zoological Museum of Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
University of Chinese Academy of Sciences, Beijing 100049, China
Funding
Yunnan Fundamental Research Projects · Strategic Priority Research Program of the Chinese Academy of Sciences · Informatization Plan of Chinese Academy of Sciences · Yunnan Technology Innovation Talent Program · Technology Support Talent Program of Chinese Academy of Sciences · Yunnan Revitalization Talent Support Program Yunling Scholar Project
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