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Snake-DETR: a lightweight and efficient model for fine-grained snake detection in complex natural environments

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成果类型:
期刊论文
作者:
Wang, Heng;Zhang, Shuai;Zhang, Cong;Liu, Zheng;Huang, Qiuxian;...
通讯作者:
Zhang, S
作者机构:
[Huang, Qiuxian; Jiang, Yiming; Zhang, Shuai; Ma, Xinyi; Wang, Heng; Liu, Zheng] Wuhan Polytech Univ, Sch Math & Comp, Wuhan 430048, Peoples R China.
[Zhang, Cong] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430048, Peoples R China.
通讯机构:
[Zhang, S ] W
Wuhan Polytech Univ, Sch Math & Comp, Wuhan 430048, Peoples R China.
语种:
英文
关键词:
Context anchor attention;Fine-grained object detection;Power-IoU;RT-DETR;Snake;Snake object detection
期刊:
Scientific Reports
ISSN:
2045-2322
年:
2025
卷:
15
期:
1
页码:
1282
基金类别:
Natural Science Foundation of Hubei Province
机构署名:
本校为第一且通讯机构
院系归属:
电气与电子工程学院
数学与计算机学院
摘要:
The rapid changes in the global environment have led to an unprecedented decline in biodiversity, with over 28% of species facing extinction. This includes snakes, which are key to ecological balance. Detecting snakes is challenging due to their camouflage and elusive nature, causing data loss and feature extraction difficulties in ecological monitoring. To address these challenges, we propose an enhanced snake detection model, Snake-DETR, based on RT-DETR, specifically designed for snake detection in complex natural environments. First, we designed the Enhanced Generalized Efficient Layer Agg...

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