ArticleOpen biology2025
Establish a simple and quantitative deep learning-based method to analyse complicated intra- and inter-species social interaction behaviour for four stag beetle species.
Article in Open biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Quantitative measurement of agonistic behaviors of intra- and interspecifics of Gryllus bimaculatus and Acheta domesticus by using DeepLabCut.Scientific reports · 2026Article
- Quantitative measurement of stag beetle behaviors in low light and complex background conditions using DAMM (detect any mouse model).Scientific reports · 2026Article
- Establish a simple and quantitative deep learning-based method to analyse complicated intra- and inter-species social interaction behaviour for four stag beetle species.Open biology · 2025Article
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4 authors.
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Abstract
Stag beetles (Lucanidae) exhibit diverse social behaviours, yet quantifying these interactions remains challenging. Understanding social interactions within and between species is crucial for comprehending their behaviour, ecology and evolution. Stag beetles exhibit diverse social behaviours, including intraspecific competition, courtship and interspecific interactions, often involving complex physical displays and subtle cues. Traditional ethological methods for analysing these behaviours are time-consuming, subjective and limited in their ability to capture the nuances of dynamic interactions. This project aims to develop a simple and quantitative deep learning-based method to analyse complicated intra- and inter-species social interaction behaviour in four stag beetle species. This study utilizes DeepLabCut™ (DLC), a state-of-the-art deep learning-based pose estimation tool, to analyse and compare intra- and inter-species social interactions in four stag beetle species:
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