LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation.
In: Pattern Recognition, Jg. 115 (2021-07-01), S. N.PAG
academicJournal
Zugriff:
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. [ABSTRACT FROM AUTHOR]
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LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation.
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Autor/in / Beteiligte Person: | Zhang, Jinghua ; Li, Chen ; Kosov, Sergey ; Grzegorzek, Marcin ; Shirahama, Kimiaki ; Jiang, Tao ; Sun, Changhao ; Li, Zihan ; Li, Hong |
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Zeitschrift: | Pattern Recognition, Jg. 115 (2021-07-01), S. N.PAG |
Veröffentlichung: | 2021 |
Medientyp: | academicJournal |
ISSN: | 0031-3203 (print) |
DOI: | 10.1016/j.patcog.2021.107885 |
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