DSC-T-Yolo-Rice: A Sand Clock Yolo Model for Rice Leaves Diseases Detection

Fan Nong Yu*, Wan Chi Shen, Arun Kumar Sangaiah, Yi Bing Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

In this study, a new Deep Sand Clock Tiny-Yolo Rice (DSC-T-yolo-Rice) network is proposed for rice leaf disease detection. Based on Tiny Yolo v4 network, the following modules are accomplished to improve the accuracy such as the Spatial Pyramid Pooling module (SPP), Convolutional Block Attention Module (CBAM), and Deep Sand Clock Feature Extraction Module (DSCFEM). Through the experimental results, it is proved that the proposed method achieves the highest test mAP.In addition, the proposed architecture in this paper focuses on the detection and analysis of key features.

原文English
主出版物標題2024 IEEE International Conference on Consumer Electronics, ICCE 2024
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350324136
DOIs
出版狀態Published - 2024
事件2024 IEEE International Conference on Consumer Electronics, ICCE 2024 - Las Vegas, 美國
持續時間: 6 1月 20248 1月 2024

出版系列

名字Digest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN(列印)0747-668X
ISSN(電子)2159-1423

Conference

Conference2024 IEEE International Conference on Consumer Electronics, ICCE 2024
國家/地區美國
城市Las Vegas
期間6/01/248/01/24

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