UAV Wheat Rust Detection based on FasterNet-YOLOv8

Huaiyu Liu; Yueyuan Zhang; Shuguang Liu; Mengyang Zhao; Lining Sun

doi:10.1109/ROBIO58561.2023.10354660

UAV Wheat Rust Detection based on FasterNet-YOLOv8

Huaiyu Liu
, Yueyuan Zhang^*
, Shuguang Liu
, Mengyang Zhao
, Lining Sun

^*Corresponding author for this work

Soochow University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

This paper introduces a UAV-based wheat rust detection system employing deep learning techniques. To address the limitations of traditional wheat rust disease detection methods, such as time and labor-intensive processes, lack of real-time monitoring, and excessive pesticide usage, In this paper, the YOLOv8 algorithm, representing the forefront of object detection methods is chosen for UAV wheat rust detection. We train the model on a prepared dataset. Subsequently, we evaluated 5 models, including YOLOv5, and YOLOv8, at two different scales (n, s) based on average precision (mAP@.5), precision, recall, and FPS. The experimental outcomes establish the superiority of the enhanced FasterNet-YOLOv8 model over YOLOv8 and YOLOv5 across all metrics, encompassing detection accuracy and processing speed. These findings affirm the viability of our suggested model within the UAV wheat rust monitoring system and underscore the efficacy of the model enhancements.

Original language	English
Title of host publication	2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023
Editors	Mehmet Dogar, Bin Fang, Dimitrios Kanoulas, Jia Pan, Alessandra Sciutti, Moju Zhao, Guanjun Bao, Bimbo Joao, Boyle Jordan Hylke, He Chen, Chen Teng, Yunduan Cui, Dagnino Giulio, Wenbo Ding, Liang Du, Farinha Andre, Yuan Gao, Hasegawa Shun, Liang He, Taogang Hou, Zhe Hu, Zhong Huang, Jackson-Mills George, Yunfeng Ji, Jirak Doreen, Feng Ju, Kaddouh Bilal, Kim Wansoo, Takuya Kiyokawa, Haiyuan Li, Peng Li, Shihao Li, Xu Li, Jianfeng Liao, Ling Jie, Chunfang Liu, Quanquan Liu, Liang Lu, Qiuyue Luo, Yudong Luo, Zebing Mao, Martinez-Hernandez Uriel, Matsuno Takahiro, Nguyen Thanh Luan, Nishio Takuzumi, Pasquali Dario, Pierella Camilla, Chao Ren, Ricci Serena, Rossini Luca, Shi Fan, Summa Susanna, Rongchuan Sun, Zhenglong Sun, Vannucci Fabio, Gang Wang, Wei Wang, Xin Wang, Yuquan Wang, Ziya Wang, Qingxiang Wu, Xiaojun Wu, Yuxin Sun, Youcan Yan, Lei Yang, Yanokura Iori, Jingfan Zhang, Shuai Zhang, Tianwei Zhang, Jinglei Zhao, Na Zhao, Chengxu Zhou, Peng Zhou, Haifei Zhu
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350325706
DOIs	https://doi.org/10.1109/ROBIO58561.2023.10354660
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023 - Koh Samui island, Thailand Duration: 4 Dec 2023 → 9 Dec 2023

Publication series

Name	2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

Conference

Conference	2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023
Country/Territory	Thailand
City	Koh Samui island
Period	4/12/23 → 9/12/23

Access to Document

10.1109/ROBIO58561.2023.10354660

Cite this

Liu, H., Zhang, Y., Liu, S., Zhao, M., & Sun, L. (2023). UAV Wheat Rust Detection based on FasterNet-YOLOv8. In M. Dogar, B. Fang, D. Kanoulas, J. Pan, A. Sciutti, M. Zhao, G. Bao, B. Joao, B. J. Hylke, H. Chen, C. Teng, Y. Cui, D. Giulio, W. Ding, L. Du, F. Andre, Y. Gao, H. Shun, L. He, T. Hou, Z. Hu, Z. Huang, J.-M. George, Y. Ji, J. Doreen, F. Ju, K. Bilal, K. Wansoo, T. Kiyokawa, H. Li, P. Li, S. Li, X. Li, J. Liao, L. Jie, C. Liu, Q. Liu, L. Lu, Q. Luo, Y. Luo, Z. Mao, M.-H. Uriel, M. Takahiro, N. T. Luan, N. Takuzumi, P. Dario, P. Camilla, C. Ren, R. Serena, R. Luca, S. Fan, S. Susanna, R. Sun, Z. Sun, V. Fabio, G. Wang, W. Wang, X. Wang, Y. Wang, Z. Wang, Q. Wu, X. Wu, Y. Sun, Y. Yan, L. Yang, Y. Iori, J. Zhang, S. Zhang, T. Zhang, J. Zhao, N. Zhao, C. Zhou, P. Zhou, ... H. Zhu (Eds.), 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023 (2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROBIO58561.2023.10354660

Liu, Huaiyu ; Zhang, Yueyuan ; Liu, Shuguang et al. / UAV Wheat Rust Detection based on FasterNet-YOLOv8. 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023. editor / Mehmet Dogar ; Bin Fang ; Dimitrios Kanoulas ; Jia Pan ; Alessandra Sciutti ; Moju Zhao ; Guanjun Bao ; Bimbo Joao ; Boyle Jordan Hylke ; He Chen ; Chen Teng ; Yunduan Cui ; Dagnino Giulio ; Wenbo Ding ; Liang Du ; Farinha Andre ; Yuan Gao ; Hasegawa Shun ; Liang He ; Taogang Hou ; Zhe Hu ; Zhong Huang ; Jackson-Mills George ; Yunfeng Ji ; Jirak Doreen ; Feng Ju ; Kaddouh Bilal ; Kim Wansoo ; Takuya Kiyokawa ; Haiyuan Li ; Peng Li ; Shihao Li ; Xu Li ; Jianfeng Liao ; Ling Jie ; Chunfang Liu ; Quanquan Liu ; Liang Lu ; Qiuyue Luo ; Yudong Luo ; Zebing Mao ; Martinez-Hernandez Uriel ; Matsuno Takahiro ; Nguyen Thanh Luan ; Nishio Takuzumi ; Pasquali Dario ; Pierella Camilla ; Chao Ren ; Ricci Serena ; Rossini Luca ; Shi Fan ; Summa Susanna ; Rongchuan Sun ; Zhenglong Sun ; Vannucci Fabio ; Gang Wang ; Wei Wang ; Xin Wang ; Yuquan Wang ; Ziya Wang ; Qingxiang Wu ; Xiaojun Wu ; Yuxin Sun ; Youcan Yan ; Lei Yang ; Yanokura Iori ; Jingfan Zhang ; Shuai Zhang ; Tianwei Zhang ; Jinglei Zhao ; Na Zhao ; Chengxu Zhou ; Peng Zhou ; Haifei Zhu. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023).

@inproceedings{387d987ce926468bb80dad4e8155fbf9,

title = "UAV Wheat Rust Detection based on FasterNet-YOLOv8",

abstract = "This paper introduces a UAV-based wheat rust detection system employing deep learning techniques. To address the limitations of traditional wheat rust disease detection methods, such as time and labor-intensive processes, lack of real-time monitoring, and excessive pesticide usage, In this paper, the YOLOv8 algorithm, representing the forefront of object detection methods is chosen for UAV wheat rust detection. We train the model on a prepared dataset. Subsequently, we evaluated 5 models, including YOLOv5, and YOLOv8, at two different scales (n, s) based on average precision (mAP@.5), precision, recall, and FPS. The experimental outcomes establish the superiority of the enhanced FasterNet-YOLOv8 model over YOLOv8 and YOLOv5 across all metrics, encompassing detection accuracy and processing speed. These findings affirm the viability of our suggested model within the UAV wheat rust monitoring system and underscore the efficacy of the model enhancements.",

author = "Huaiyu Liu and Yueyuan Zhang and Shuguang Liu and Mengyang Zhao and Lining Sun",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023 ; Conference date: 04-12-2023 Through 09-12-2023",

year = "2023",

doi = "10.1109/ROBIO58561.2023.10354660",

language = "英语",

series = "2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Mehmet Dogar and Bin Fang and Dimitrios Kanoulas and Jia Pan and Alessandra Sciutti and Moju Zhao and Guanjun Bao and Bimbo Joao and Hylke, \{Boyle Jordan\} and He Chen and Chen Teng and Yunduan Cui and Dagnino Giulio and Wenbo Ding and Liang Du and Farinha Andre and Yuan Gao and Hasegawa Shun and Liang He and Taogang Hou and Zhe Hu and Zhong Huang and Jackson-Mills George and Yunfeng Ji and Jirak Doreen and Feng Ju and Kaddouh Bilal and Kim Wansoo and Takuya Kiyokawa and Haiyuan Li and Peng Li and Shihao Li and Xu Li and Jianfeng Liao and Ling Jie and Chunfang Liu and Quanquan Liu and Liang Lu and Qiuyue Luo and Yudong Luo and Zebing Mao and Martinez-Hernandez Uriel and Matsuno Takahiro and Luan, \{Nguyen Thanh\} and Nishio Takuzumi and Pasquali Dario and Pierella Camilla and Chao Ren and Ricci Serena and Rossini Luca and Shi Fan and Summa Susanna and Rongchuan Sun and Zhenglong Sun and Vannucci Fabio and Gang Wang and Wei Wang and Xin Wang and Yuquan Wang and Ziya Wang and Qingxiang Wu and Xiaojun Wu and Yuxin Sun and Youcan Yan and Lei Yang and Yanokura Iori and Jingfan Zhang and Shuai Zhang and Tianwei Zhang and Jinglei Zhao and Na Zhao and Chengxu Zhou and Peng Zhou and Haifei Zhu",

booktitle = "2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023",

address = "美国",

}

Liu, H, Zhang, Y, Liu, S, Zhao, M & Sun, L 2023, UAV Wheat Rust Detection based on FasterNet-YOLOv8. in M Dogar, B Fang, D Kanoulas, J Pan, A Sciutti, M Zhao, G Bao, B Joao, BJ Hylke, H Chen, C Teng, Y Cui, D Giulio, W Ding, L Du, F Andre, Y Gao, H Shun, L He, T Hou, Z Hu, Z Huang, J-M George, Y Ji, J Doreen, F Ju, K Bilal, K Wansoo, T Kiyokawa, H Li, P Li, S Li, X Li, J Liao, L Jie, C Liu, Q Liu, L Lu, Q Luo, Y Luo, Z Mao, M-H Uriel, M Takahiro, NT Luan, N Takuzumi, P Dario, P Camilla, C Ren, R Serena, R Luca, S Fan, S Susanna, R Sun, Z Sun, V Fabio, G Wang, W Wang, X Wang, Y Wang, Z Wang, Q Wu, X Wu, Y Sun, Y Yan, L Yang, Y Iori, J Zhang, S Zhang, T Zhang, J Zhao, N Zhao, C Zhou, P Zhou & H Zhu (eds), 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023. 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023, Koh Samui island, Thailand, 4/12/23. https://doi.org/10.1109/ROBIO58561.2023.10354660

UAV Wheat Rust Detection based on FasterNet-YOLOv8. / Liu, Huaiyu; Zhang, Yueyuan; Liu, Shuguang et al.
2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023. ed. / Mehmet Dogar; Bin Fang; Dimitrios Kanoulas; Jia Pan; Alessandra Sciutti; Moju Zhao; Guanjun Bao; Bimbo Joao; Boyle Jordan Hylke; He Chen; Chen Teng; Yunduan Cui; Dagnino Giulio; Wenbo Ding; Liang Du; Farinha Andre; Yuan Gao; Hasegawa Shun; Liang He; Taogang Hou; Zhe Hu; Zhong Huang; Jackson-Mills George; Yunfeng Ji; Jirak Doreen; Feng Ju; Kaddouh Bilal; Kim Wansoo; Takuya Kiyokawa; Haiyuan Li; Peng Li; Shihao Li; Xu Li; Jianfeng Liao; Ling Jie; Chunfang Liu; Quanquan Liu; Liang Lu; Qiuyue Luo; Yudong Luo; Zebing Mao; Martinez-Hernandez Uriel; Matsuno Takahiro; Nguyen Thanh Luan; Nishio Takuzumi; Pasquali Dario; Pierella Camilla; Chao Ren; Ricci Serena; Rossini Luca; Shi Fan; Summa Susanna; Rongchuan Sun; Zhenglong Sun; Vannucci Fabio; Gang Wang; Wei Wang; Xin Wang; Yuquan Wang; Ziya Wang; Qingxiang Wu; Xiaojun Wu; Yuxin Sun; Youcan Yan; Lei Yang; Yanokura Iori; Jingfan Zhang; Shuai Zhang; Tianwei Zhang; Jinglei Zhao; Na Zhao; Chengxu Zhou; Peng Zhou; Haifei Zhu. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - UAV Wheat Rust Detection based on FasterNet-YOLOv8

AU - Liu, Huaiyu

AU - Zhang, Yueyuan

AU - Liu, Shuguang

AU - Zhao, Mengyang

AU - Sun, Lining

PY - 2023

Y1 - 2023

N2 - This paper introduces a UAV-based wheat rust detection system employing deep learning techniques. To address the limitations of traditional wheat rust disease detection methods, such as time and labor-intensive processes, lack of real-time monitoring, and excessive pesticide usage, In this paper, the YOLOv8 algorithm, representing the forefront of object detection methods is chosen for UAV wheat rust detection. We train the model on a prepared dataset. Subsequently, we evaluated 5 models, including YOLOv5, and YOLOv8, at two different scales (n, s) based on average precision (mAP@.5), precision, recall, and FPS. The experimental outcomes establish the superiority of the enhanced FasterNet-YOLOv8 model over YOLOv8 and YOLOv5 across all metrics, encompassing detection accuracy and processing speed. These findings affirm the viability of our suggested model within the UAV wheat rust monitoring system and underscore the efficacy of the model enhancements.

AB - This paper introduces a UAV-based wheat rust detection system employing deep learning techniques. To address the limitations of traditional wheat rust disease detection methods, such as time and labor-intensive processes, lack of real-time monitoring, and excessive pesticide usage, In this paper, the YOLOv8 algorithm, representing the forefront of object detection methods is chosen for UAV wheat rust detection. We train the model on a prepared dataset. Subsequently, we evaluated 5 models, including YOLOv5, and YOLOv8, at two different scales (n, s) based on average precision (mAP@.5), precision, recall, and FPS. The experimental outcomes establish the superiority of the enhanced FasterNet-YOLOv8 model over YOLOv8 and YOLOv5 across all metrics, encompassing detection accuracy and processing speed. These findings affirm the viability of our suggested model within the UAV wheat rust monitoring system and underscore the efficacy of the model enhancements.

UR - https://www.scopus.com/pages/publications/85182556666

U2 - 10.1109/ROBIO58561.2023.10354660

DO - 10.1109/ROBIO58561.2023.10354660

M3 - 会议稿件

AN - SCOPUS:85182556666

T3 - 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

BT - 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

A2 - Dogar, Mehmet

A2 - Fang, Bin

A2 - Kanoulas, Dimitrios

A2 - Pan, Jia

A2 - Sciutti, Alessandra

A2 - Zhao, Moju

A2 - Bao, Guanjun

A2 - Joao, Bimbo

A2 - Hylke, Boyle Jordan

A2 - Chen, He

A2 - Teng, Chen

A2 - Cui, Yunduan

A2 - Giulio, Dagnino

A2 - Ding, Wenbo

A2 - Du, Liang

A2 - Andre, Farinha

A2 - Gao, Yuan

A2 - Shun, Hasegawa

A2 - He, Liang

A2 - Hou, Taogang

A2 - Hu, Zhe

A2 - Huang, Zhong

A2 - George, Jackson-Mills

A2 - Ji, Yunfeng

A2 - Doreen, Jirak

A2 - Ju, Feng

A2 - Bilal, Kaddouh

A2 - Wansoo, Kim

A2 - Kiyokawa, Takuya

A2 - Li, Haiyuan

A2 - Li, Peng

A2 - Li, Shihao

A2 - Li, Xu

A2 - Liao, Jianfeng

A2 - Jie, Ling

A2 - Liu, Chunfang

A2 - Liu, Quanquan

A2 - Lu, Liang

A2 - Luo, Qiuyue

A2 - Luo, Yudong

A2 - Mao, Zebing

A2 - Uriel, Martinez-Hernandez

A2 - Takahiro, Matsuno

A2 - Luan, Nguyen Thanh

A2 - Takuzumi, Nishio

A2 - Dario, Pasquali

A2 - Camilla, Pierella

A2 - Ren, Chao

A2 - Serena, Ricci

A2 - Luca, Rossini

A2 - Fan, Shi

A2 - Susanna, Summa

A2 - Sun, Rongchuan

A2 - Sun, Zhenglong

A2 - Fabio, Vannucci

A2 - Wang, Gang

A2 - Wang, Wei

A2 - Wang, Xin

A2 - Wang, Yuquan

A2 - Wang, Ziya

A2 - Wu, Qingxiang

A2 - Wu, Xiaojun

A2 - Sun, Yuxin

A2 - Yan, Youcan

A2 - Yang, Lei

A2 - Iori, Yanokura

A2 - Zhang, Jingfan

A2 - Zhang, Shuai

A2 - Zhang, Tianwei

A2 - Zhao, Jinglei

A2 - Zhao, Na

A2 - Zhou, Chengxu

A2 - Zhou, Peng

A2 - Zhu, Haifei

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

Y2 - 4 December 2023 through 9 December 2023

ER -

Liu H, Zhang Y, Liu S, Zhao M, Sun L. UAV Wheat Rust Detection based on FasterNet-YOLOv8. In Dogar M, Fang B, Kanoulas D, Pan J, Sciutti A, Zhao M, Bao G, Joao B, Hylke BJ, Chen H, Teng C, Cui Y, Giulio D, Ding W, Du L, Andre F, Gao Y, Shun H, He L, Hou T, Hu Z, Huang Z, George JM, Ji Y, Doreen J, Ju F, Bilal K, Wansoo K, Kiyokawa T, Li H, Li P, Li S, Li X, Liao J, Jie L, Liu C, Liu Q, Lu L, Luo Q, Luo Y, Mao Z, Uriel MH, Takahiro M, Luan NT, Takuzumi N, Dario P, Camilla P, Ren C, Serena R, Luca R, Fan S, Susanna S, Sun R, Sun Z, Fabio V, Wang G, Wang W, Wang X, Wang Y, Wang Z, Wu Q, Wu X, Sun Y, Yan Y, Yang L, Iori Y, Zhang J, Zhang S, Zhang T, Zhao J, Zhao N, Zhou C, Zhou P, Zhu H, editors, 2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023). doi: 10.1109/ROBIO58561.2023.10354660

UAV Wheat Rust Detection based on FasterNet-YOLOv8

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