Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder.
(2021)
Journal Article
LIU, Z., THEVAR, T., TAKAHASHI, T., BURNS, N., YAMADA, T., SANGEKAR, M., LINDSAY, D., WATSON, J. and 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 [online], 38(10), pages 1570-1580. Available from: https://doi.org/10.1364/JOSAA.424271
Digital holography is a useful tool to image microscopic particles.Reconstructed holograms give high-resolution shape information that can beused to identify the types of particles. However, the process ofreconstructing holograms is computationally i... Read More about Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder..