Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder

Liu, ZonghuaThevar, ThangavelTakahashi, TomokoBurns, NicholasYamada, TakakiSangekar, MehulLindsay, DhugalWatson, JohnThornton, Blair2022-09-262022-09-262021-10-01Liu, Z, Thevar, T, Takahashi, T, Burns, N, Yamada, T, Sangekar, M, Lindsay, D, Watson, J & Thornton, B 2021, 'Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder', Journal of the Optical Society of America A: Optics and Image Science, and Vision, vol. 38, no. 10, pp. 1570-1580. https://doi.org/10.1364/JOSAA.4242711084-7529https://hdl.handle.net/2164/19226Acknowledgment. This work is funded by a joint UK-Japan research program (NERC-JST SICORP Marine Sensor Proof of Concept under project code NE/R01227X/1).114725129engTA Engineering (General). Civil engineering (General)Electronic, Optical and Magnetic MaterialsAtomic and Molecular Physics, and OpticsComputer Vision and Pattern RecognitionNatural Environment Research Council (NERC)NE/R01227X/1TAUnsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoderJournal article10.1364/JOSAA.424271http://www.scopus.com/inward/record.url?scp=85116346519&partnerID=8YFLogxK3810