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

Files in This Item:
File Description SizeFormat 
FullText.pdfEmbargoed until 21 Apr 2022516.5 kBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.