Intelligent Grazing UAV Based on Airborne Depth Reasoning
文献类型：期刊论文
| 作者 | Luo, Wei1,2,3,4; Zhang, Ze1; Fu, Ping5; Wei, Guosheng1; Wang, Dongliang2; Li, Xuqing1,3,4; Shao, Quanqin2,6; He, Yuejun1,3,4; Wang, Huijuan1; Zhao, Zihui1,3,4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-09-01 |
| 卷号 | 14期号:17页码:17 |
| 关键词 | precision grazing intelligent UAV cattle monitoring YOLOv5 Inception V3 LSTM |
| DOI | 10.3390/rs14174188 |
| 通讯作者 | Wang, Dongliang(wangdongliang@igsnrr.ac.cn) |
| 英文摘要 | The existing precision grazing technology helps to improve the utilization rate of livestock to pasture, but it is still at the level of "collectivization" and cannot provide more accurate grazing management and control. (1) Background: In recent years, with the rapid development of agent-related technologies such as deep learning, visual navigation and tracking, more and more lightweight edge computing cell target detection algorithms have been proposed. (2) Methods: In this study, the improved YOLOv5 detector combined with the extended dataset realized the accurate identification and location of domestic cattle; with the help of the kernel correlation filter (KCF) automatic tracking framework, the long-term cyclic convolution network (LRCN) was used to analyze the texture characteristics of animal fur and effectively distinguish the individual cattle. (3) Results: The intelligent UAV equipped with an AGX Xavier high-performance computing unit ran the above algorithm through edge computing and effectively realized the individual identification and positioning of cattle during the actual flight. (4) Conclusion: The UAV platform based on airborne depth reasoning is expected to help the development of smart ecological animal husbandry and provide better precision services for herdsmen. |
| WOS关键词 | ANIMAL IDENTIFICATION ; FACE RECOGNITION ; EAR TAGS ; BEHAVIOR ; TRACKING ; SYSTEM |
| 资助项目 | Chengdu, China |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000851860200001 |
| 出版者 | MDPI |
| 资助机构 | Chengdu, China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/182793]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Dongliang |
| 作者单位 | 1.North China Inst Aerosp Engn, Langfang 065000, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 3.Aerosp Remote Sensing Informat Proc & Applicat Co, Langfang 065000, Peoples R China 4.Natl Joint Engn Res Ctr Space Remote Sensing Info, Langfang 065000, Peoples R China 5.Minjiang Univ, Fujian Prov Educ Dept, Key Lab Adv Mot Control, Fuzhou 350108, Peoples R China 6.Univ Chinese Acad Sci, Beijing 101407, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Wei,Zhang, Ze,Fu, Ping,et al. Intelligent Grazing UAV Based on Airborne Depth Reasoning[J]. REMOTE SENSING,2022,14(17):17. |
| APA | Luo, Wei.,Zhang, Ze.,Fu, Ping.,Wei, Guosheng.,Wang, Dongliang.,...&Liu, Xueli.(2022).Intelligent Grazing UAV Based on Airborne Depth Reasoning.REMOTE SENSING,14(17),17. |
| MLA | Luo, Wei,et al."Intelligent Grazing UAV Based on Airborne Depth Reasoning".REMOTE SENSING 14.17(2022):17. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。