A deep learning framework for autonomous flame detection

Li, Z., Mihaylova, L. orcid.org/0000-0001-5856-2223 and Yang, L. (2021) A deep learning framework for autonomous flame detection. Neurocomputing, 448. pp. 205-216. ISSN 0925-2312



Copyright, Publisher and Additional Information: © 2021 Published by Elsevier B.V. This is an author produced version of a paper subsequently published in Neurocomputing. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Flame detection; Flame R-CNN; Dirichlet process Gaussian mixture model; Variational inference
  • Accepted: 5 March 2021
  • Published (online): 16 March 2021
  • Published: 11 August 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Science Research CouncilEP/T013265/1
Depositing User: Symplectic Sheffield
Date Deposited: 15 Mar 2021 09:06
Last Modified: 16 Mar 2022 01:38
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.neucom.2021.03.019


Filename: FlameRCNN.pdf

Licence: CC-BY-NC-ND 4.0