Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention.

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第一作者： Junjie,He

第一单位： College of Tea Science, Yunnan Agricultural University, Kunming, China.;Key Laboratory of Intelligent Organic Tea Garden Construction in University of Yunnan Province, Yunnan Agricultural University, Kunming, China.

作者： Junjie,He ^[1] ; Shihao,Zhang ^[2] ; Chunhua,Yang ^[1] ; Houqiao,Wang ^[1] ; Jun,Gao ^[3] ; Wei,Huang ^[3] ; Qiaomei,Wang ^[3] ; Xinghua,Wang ^[3] ; Wenxia,Yuan ^[3] ; Yamin,Wu ^[1] ; Lei,Li ^[1] ; Jiayi,Xu ^[1] ; Zejun,Wang ^[1] ; Rukui,Zhang ^[3] ; Baijuan,Wang ^[1]

作者单位： College of Tea Science, Yunnan Agricultural University, Kunming, China.;Key Laboratory of Intelligent Organic Tea Garden Construction in University of Yunnan Province, Yunnan Agricultural University, Kunming, China. ^[1] Key Laboratory of Intelligent Organic Tea Garden Construction in University of Yunnan Province, Yunnan Agricultural University, Kunming, China. ^[2] College of Tea Science, Yunnan Agricultural University, Kunming, China. ^[3]

关键词 MPDIou Spatial and Channel Reconstruction Convolution improved Yolov7 pest identification vision transformer with Bi-Level Routing Attention

DOI 10.3389/fpls.2024.1327237

PMID 38379942

发布时间 2024-02-22

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Frontiers in plant science

2024年15卷

1327237页

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Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention.

Frontiers in plant science

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Frontiers in plant science

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Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention.

Frontiers in plant science

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Frontiers in plant science

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