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A deep learning lightweight model for real-time captive macaque facial recognition based on an improved YOLOX model
Zhang, JJ; Gao, Y; Zhang, BL; Wu, DD
2025
发表期刊ZOOLOGICAL RESEARCH
ISSN2095-8137
卷号46期号:2页码:339-354
摘要Automated behavior monitoring of macaques offers transformative potential for advancing biomedical research and animal welfare. However, reliably identifying individual macaques in group environments remains a significant challenge. This study introduces ACE-YOLOX, a lightweight facial recognition model tailored for captive macaques. ACE-YOLOX incorporates Efficient Channel Attention (ECA), Complete Intersection over Union loss (CIoU), and Adaptive Spatial Feature Fusion (ASFF) into the YOLOX framework, enhancing prediction accuracy while reducing computational complexity. These integrated approaches enable effective multiscale feature extraction. Using a dataset comprising 179 400 labeled facial images from 1 196 macaques, ACE-YOLOX surpassed the performance of classical object detection models, demonstrating superior accuracy and real-time processing capabilities. An Android application was also developed to deploy ACE-YOLOX on smartphones, enabling on-device, real-time macaque recognition. Our experimental results highlight the potential of ACE-YOLOX as a non-invasive identification tool, offering an important foundation for future studies in macaque facial expression recognition, cognitive psychology, and social behavior.
收录类别SCI
语种英语
文献类型期刊论文
条目标识符http://ir.kiz.ac.cn/handle/152453/14521
专题科研部门_进化与发育转录组学(吴东东)
推荐引用方式
GB/T 7714
Zhang, JJ,Gao, Y,Zhang, BL,et al. A deep learning lightweight model for real-time captive macaque facial recognition based on an improved YOLOX model[J]. ZOOLOGICAL RESEARCH,2025,46(2):339-354.
APA Zhang, JJ,Gao, Y,Zhang, BL,&Wu, DD.(2025).A deep learning lightweight model for real-time captive macaque facial recognition based on an improved YOLOX model.ZOOLOGICAL RESEARCH,46(2),339-354.
MLA Zhang, JJ,et al."A deep learning lightweight model for real-time captive macaque facial recognition based on an improved YOLOX model".ZOOLOGICAL RESEARCH 46.2(2025):339-354.
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