Multi-scale fusion CNN for Lanzhou Lily Diseases Detection

doi:10.1117/12.3029856

	Multi-scale fusion CNN for Lanzhou Lily Diseases Detection
	Zhang, Jingjing 1; Bai, Yuqing 2; Yang, Wentao 2; Ding, Yongjun2
	2024
会议名称	2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024
会议录名称	Proceedings of SPIE - The International Society for Optical Engineering
卷号	13167
会议日期	January 19, 2024 - January 21, 2024
会议地点	Xiamen, China
会议录编者/会议主办者	Academic Exchange Information Centre (AEIC) ; Shandong University
出版者	SPIE
摘要	Lanzhou lily is the only kind of sweet lily in China. However, its yield and quality have decreased significantly in recent years due to gray mold disease, bulb rot disease and other diseases. In order to improve the anti-interference ability of Lanzhou lily diseases diagnosis model, only 4, 8, 16, 32, 32 feature maps were selected from the VGG16 model's five pooling layers removing 75% of all feature maps. In the process of fusion, it was found that the average pooling was better than the maximum pooling and the maximum feature selection was superior to random feature selection in the analysis of the diagnosis accuracy and anti-noise performance. The result shown that the accuracy of Lanzhou lily diseases diagnosis reached 97.82% by using the multi-scale fusion CNN with the average pooling and maximum feature selection. In addition, the anti-interference ability of Multi-scale fusion CNN was obviously better than that of VGG 16 model for Gaussian noise, salt-and-pepper noise and speckle noise. The diagnosis CNN constructed in this paper can provide technical support for digitized field management of Lanzhou lily. © 2024 SPIE.
关键词	Feature extraction Gaussian noise (electronic) Molds Anti-interference Bulb rot disease Component Disease diagnosis Features selection Grey mold disease Lanzhou Lanzhou lily Multiscale fusion Rot disease
DOI	10.1117/12.3029856
收录类别	EI
语种	英语
EI入藏号	20242716656786
EI主题词	Salt and pepper noise
原始文献类型	Conference article (CA)
EISSN	1996-756X
ISSN	0277-786X
文献类型	会议论文
条目标识符	https://ir.nwnu.edu.cn/handle/39RV6HYL/98802
专题	实体学院_计算机科学与工程学院
通讯作者	Ding, Yongjun
作者单位	1.School of Electronic and Information Engineering, Lanzhou City University, Lanzhou, China; 2.College of Computer Science & Engineering, Northwest Normal University, Lanzhou, China
通讯作者单位	计算机科学与工程学院
推荐引用方式 GB/T 7714	Zhang, Jingjing,Bai, Yuqing,Yang, Wentao,et al. Multi-scale fusion CNN for Lanzhou Lily Diseases Detection[C]//Academic Exchange Information Centre (AEIC), Shandong University:SPIE,2024.