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LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation
Zhang, Jinghua1; Li, Chen1; Kosov, Sergey2; Grzegorzek, Marcin3; Shirahama, Kimiaki4; Jiang, Tao5; Sun, Changhao1,6; Li, Zihan1; Li, Hong1
Department其他
Source PublicationPattern Recognition
ISSN0031-3203
2021
Volume115Pages:1-17
Indexed BySCI ; EI
EI Accession number20211010037863
WOS IDWOS:000639745600011
Contribution Rank6
Funding OrganizationNational Natural Science Foundation of China (No. 61806047)
KeywordEnvironmental miroorganisms Image segmentation Deep convolutional neural networks Low-cost
Abstract

In this paper, we propose a novel Low-cost U-Net (LCU-Net) for the Environmental Microorganism (EM) image segmentation task to assist microbiologists in detecting and identifying EMs more effectively. The LCU-Net is an improved Convolutional Neural Network (CNN) based on U-Net, Inception, and concatenate operations. It addresses the limitation of single receptive field setting and the relatively high memory cost of U-Net. Experimental results show the effectiveness and potential of the proposed LCU-Net in the practical EM image segmentation field.

Language英语
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS KeywordCLASSIFICATION
WOS Research AreaComputer Science ; Engineering
Funding ProjectNational Natural Science Foundation of China[61806047]
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28500
Collection其他
Corresponding AuthorLi, Chen
Affiliation1.Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
2.Faculty of Data Engineering, Jacobs University Bremen, Bremen, Germany
3.Institute of Medical Informatics, University of Luebeck, Luebeck, Germany
4.Faculty of Science and Engineering, Kindai University, Higashiosaka, Osaka, Japan
5.Control Engineering College, Chengdu University of Information Technology, Chengdu, China
6.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Zhang, Jinghua,Li, Chen,Kosov, Sergey,et al. LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation[J]. Pattern Recognition,2021,115:1-17.
APA Zhang, Jinghua.,Li, Chen.,Kosov, Sergey.,Grzegorzek, Marcin.,Shirahama, Kimiaki.,...&Li, Hong.(2021).LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation.Pattern Recognition,115,1-17.
MLA Zhang, Jinghua,et al."LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation".Pattern Recognition 115(2021):1-17.
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