Preprint Highlight: Learning orientation-invariant representations enables accurate and robust morphologic profiling of cells and organelles
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DOI: 10.1091/mbc.p23-04-0013
Abstract: One application of deep learning in analysis of cell biological microscopy data is developing meaningful quantitative representations of cellular and/or molecular phenotypic signatures. Because image orientation has no relevance for shape and morphology, encoding orientation… read more here.
Keywords: preprint highlight; invariant representations; learning orientation; orientation invariant ... See more keywords