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Disease Detection and Identification of Rice Leaf Based on Improved Detection Transformer

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成果类型:
期刊论文
作者:
Yang, Hua;Deng, Xingquan;Shen, Hao;Lei, Qingfeng;Zhang, Shuxiang;...
通讯作者:
Yang, H
作者机构:
[Deng, Xingquan; Yang, Hua; Yang, H; Lei, Qingfeng; Zhang, Shuxiang; Liu, Neng] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China.
[Shen, Hao] Baijuncheng Technol Co Ltd, Wuhan 434000, Peoples R China.
通讯机构:
[Yang, H ] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430040, Peoples R China.
语种:
英文
关键词:
rice leaf disease diagnosis;object detection;DETR;deep learning;image processing
期刊:
Agriculture-Basel
ISSN:
2077-0472
年:
2023
卷:
13
期:
7
页码:
1361-
基金类别:
Conceptualization, H.Y. and X.D.; methodology, X.D.; software, H.Y. and S.Z.; validation, X.D., H.S. and N.L.; formal analysis, X.D.; investigation, Q.L.; resources, H.Y.; data curation, X.D. and H.S.; writing—original draft preparation, H.Y.; writing—review and editing, X.D.; visualization, S.Z.; supervision, H.Y.; project administration, H.Y.; funding acquisition, H.Y. All authors have read and agreed to the published version of the manuscript. This research was funded by the School enterprise cooperation project (No.whpu-2021-kj-762 and 1145, No.whpu-2022-kj-1586 and 2153), Hubei Provincial Teaching and Research Project (No.2018368) and Ministry of Education Industry-University Cooperation Collaborative Education Project(No. 220900786024216).
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
In recent years, the domain of diagnosing plant afflictions has predominantly relied upon the utilization of deep learning techniques for classifying images of diseased specimens; however, these classification algorithms remain insufficient for instances where a single plant exhibits multiple ailments. Consequently, we view the region afflicted by the malady of rice leaves as a minuscule issue of target detection, and then avail ourselves of a computational approach to vision to identify the affected area. In this paper, we advance a proposal for a Dense Higher-Level Composition Feature Pyrami...

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