Machine learning for improved size estimation of complex marine particles from noisy holographic images
| dc.contributor.author | Liu, Zonghua | |
| dc.contributor.author | Takeuchi, Marika | |
| dc.contributor.author | Contreras, Yéssica | |
| dc.contributor.author | Thevar, Thangavel | |
| dc.contributor.author | Nimmo-Smith, Alex | |
| dc.contributor.author | Watson, John | |
| dc.contributor.author | Giering, Sarah L. C. | |
| dc.contributor.institution | University of Aberdeen.Engineering | en |
| dc.contributor.institution | University of Aberdeen.Engineering | en |
| dc.date.accessioned | 2025-08-18T10:34:02Z | |
| dc.date.available | 2025-08-18T10:34:02Z | |
| dc.date.issued | 2025-08-15 | |
| dc.description | We thank Richard Lampitt, Morten Iversen and Kevin Saw for the deployment of the Red Camera Frame, and the captain, crew and scientists of the research cruise DY086. Our thanks extend to Nick Burns and Mike Ockwell from Hi-Z 3D LTD (London, UK) for their contributions in developing FastScan that significantly facilitates hologram process. | en |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 16 | |
| dc.format.extent | 8139263 | |
| dc.identifier | 308017398 | |
| dc.identifier | f8a45416-86aa-49d8-b97b-9343f25ed222 | |
| dc.identifier | 105014607185 | |
| dc.identifier.citation | Liu, Z, Takeuchi, M, Contreras, Y, Thevar, T, Nimmo-Smith, A, Watson, J & Giering, S L C 2025, 'Machine learning for improved size estimation of complex marine particles from noisy holographic images', Frontiers in Marine Science, vol. 12, 1587939. https://doi.org/10.3389/fmars.2025.1587939 | en |
| dc.identifier.doi | 10.3389/fmars.2025.1587939 | |
| dc.identifier.issn | 2296-7745 | |
| dc.identifier.other | RIS: urn:7A15242E2B0495107404A0E0DF0F453D | |
| dc.identifier.uri | https://hdl.handle.net/2164/25869 | |
| dc.identifier.vol | 12 | en |
| dc.language.iso | eng | |
| dc.relation.ispartof | Frontiers in Marine Science | en |
| dc.subject | SDG 14 - Life Below Water | en |
| dc.subject | subsea digital holography | en |
| dc.subject | hologram processing | en |
| dc.subject | machine learning | en |
| dc.subject | size estimation | en |
| dc.subject | particle size distributions | en |
| dc.subject | GC Oceanography | en |
| dc.subject.lcc | GC | en |
| dc.title | Machine learning for improved size estimation of complex marine particles from noisy holographic images | en |
| dc.type | Journal article | en |
Files
Original bundle
1 - 1 of 1
- Name:
- Liu_etal_FiMS_Machine_Learning_for_VOR.pdf
- Size:
- 7.76 MB
- Format:
- Adobe Portable Document Format