Number 104, Septembre-Octobre 2020
|Page(s)||30 - 33|
|Section||Focus: Photonics and Artificial intelligence|
|Published online||09 November 2020|
Free annotated data for deep learning in microscopy? A hitchhiker’s guide
Idiap Research Institute, Rue Marconi 19, 1920 Martigny, Switzerland
2 École Polytechnique Fédérale de Lausanne (EPFL), Route Cantonale, 1015 Lausanne, Switzerland
3 University of California, Santa Barbara, CA 93106-9010, USA
* e-mail : firstname.lastname@example.org
In microscopy, the time burden and cost of acquiring and annotating large datasets that many deep learning models take as a prerequisite, often appears to make these methods impractical. Can this requirement for annotated data be relaxed? Is it possible to borrow the knowledge gathered from datasets in other application fields and leverage it for microscopy? Here, we aim to provide an overview of methods that have recently emerged to successfully train learning-based methods in bio-microscopy.
© The authors, published by EDP Sciences, 2020
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