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Keypoint-Based Forest Musk Deer Behavioral Recognition Method

delete2026-05-24
delete0
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OA
AI
D
Dequan Guo
C
Chuankang Chen
郑承利 封面图
郑承利 (Chengli Zheng)
Z
Zhenyu Wang
张大鹏 封面图
张大鹏 (Dapeng Zhang)
D
Dening Luo *
DOI：10.3390/ani16111594delete
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摘要

摘要

En 中文
传统林麝行为监测依赖人工观察或视频回放，存在效率低、主观性强及难以实时预警等问题，从而限制了繁育和保育工作的开展。为解决这些问题，本研究提出了一种基于改进YOLOv8-Pose的行为识别方法。通过构建涵盖四种行为的关鍵点数据集并引入优化模块，提升了目标检测和姿态估计的精度，性能优于多个现有模型。同时开发了可视化界面，为林麝的人工繁育和野外保育提供了高效、低成本的自动化分析工具，从而为濒危物种的智能化保护做出贡献。
Keyword:
musk deer
keypoint detection
improved YOLOv8-Pose
behavioral recognition
real-time monitoring

期刊

Animals 封面图
Animals
IF:
2.7
论文数:
6.3K
被引数:
5.1W

机构

S
Sichuan Institute for Drug Control
学者数:
16
论文数: 15
被引数: 0
C
chengdu university of information technology
学者数:
836
论文数: 330
被引数: 0
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