Pitkäaho, Tomi and Manninen, Aki and Naughton, Thomas J. (2018) Classification of Digital Holograms with Deep Learning and Hand-Crafted Features. In: Digital Holography and Three- Dimensional Imaging 2018 (part of Imaging and Applied Optics 2018), 2018.
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Abstract
Digital holographic microscopy allows a single-shot label-free imaging of living microscopic objects using a low intensity laser. Using reconstructed quantitative phase as an input to a convolutional neural network, detection of tumorigenic samples is possible.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | Classification; Digital Holograms; Deep Learning; Hand-Crafted Features; |
Academic Unit: | Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 15593 |
Identification Number: | https://doi.org/10.1364/DH.2018.DW2F.3 |
Depositing User: | Thomas Naughton |
Date Deposited: | 28 Feb 2022 15:56 |
Refereed: | Yes |
URI: | |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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