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- W3006582843 abstract "Deep learning-based data analysis methods have gained considerable attention in all fields of science over the last decade. In recent years, this trend has reached the single-molecule community. In this review, we will survey significant contributions of the application of deep learning in single-molecule imaging experiments. Additionally, we will describe the historical events that led to the development of modern deep learning methods, summarize the fundamental concepts of deep learning, and highlight the importance of proper data composition for accurate, unbiased results." @default.
- W3006582843 created "2020-02-24" @default.
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- W3006582843 date "2020-02-27" @default.
- W3006582843 modified "2023-10-16" @default.
- W3006582843 title "Deep learning in single-molecule microscopy: fundamentals, caveats, and recent developments [Invited]" @default.
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- W3006582843 doi "https://doi.org/10.1364/boe.386361" @default.
- W3006582843 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7075610" @default.
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