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http://bura.brunel.ac.uk/handle/2438/23492Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zeng, N | - |
| dc.contributor.author | Li, H | - |
| dc.contributor.author | Wang, Z | - |
| dc.contributor.author | Liu, W | - |
| dc.contributor.author | Liu, S | - |
| dc.contributor.author | Alsaadi, FE | - |
| dc.contributor.author | Liu, X | - |
| dc.date.accessioned | 2021-11-12T22:08:51Z | - |
| dc.date.available | 2021-11-12T22:08:51Z | - |
| dc.date.issued | 2020-04-21 | - |
| dc.identifier.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. | en_US |
| dc.identifier.issn | 0925-2312 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23492 | - |
| dc.description.sponsorship | International Science and Technology Cooperation Project of Fujian Province of China under Grant 2019I0003; Korea Foundation for Advanced Studies, in part by the Fundamental Research Funds for the Central Universities of China under Grant 20720190009; The Open Fund of Engineering Research Center of Big Data Application in Private Health Medicine of China under Grant KF2020002; The Open Fund of Provincial Key Laboratory of Eco-Industrial Green Technology-Wuyi University of China. | en_US |
| dc.format.extent | 173 - 180 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Elsevier BV | en_US |
| dc.rights | © 2020 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.neucom.2020.04.001 | - |
| dc.subject | deep reinforcement learning | en_US |
| dc.subject | image segmentation | en_US |
| dc.subject | deep belief network | en_US |
| dc.subject | multi-factor learning curve | en_US |
| dc.subject | gold immunochromatographic strip | en_US |
| dc.title | Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1016/j.neucom.2020.04.001 | - |
| dc.relation.isPartOf | Neurocomputing | - |
| pubs.publication-status | Published | - |
| pubs.volume | 425 | - |
| dc.identifier.eissn | 1872-8286 | - |
| Appears in Collections: | Dept of Computer Science Embargoed Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Embargoed until 21 Apr 2022 | 516.5 kB | Adobe PDF | View/Open |
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