Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/23492
Title: | Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip |
Authors: | Zeng, N Li, H Wang, Z Liu, W Liu, S Alsaadi, FE Liu, X |
Keywords: | deep reinforcement learning;image segmentation;deep belief network;multi-factor learning curve;gold immunochromatographic strip |
Issue Date: | 21-Apr-2020 |
Publisher: | Elsevier BV |
Citation: | Zeng, N., Li, H., Wang, Z., Liu, W., Liu, S., Alsaadi, F.E. and Liu, X. (2021) 'Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip', Neurocomputing, 425, pp. 173 - 180. doi: 10.1016/j.neucom.2020.04.001. |
URI: | https://bura.brunel.ac.uk/handle/2438/23492 |
DOI: | https://doi.org/10.1016/j.neucom.2020.04.001 |
ISSN: | 0925-2312 |
Appears in Collections: | Dept of Computer Science Embargoed Research Papers |
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FullText.pdf | Embargoed until 21 Apr 2022 | 516.5 kB | Adobe PDF | View/Open |
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