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Advances in artificial intelligence in microscopy

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Artificial Intelligence is pushing the limits of what microscopy-based imaging can do for analysing and quantifying biological data.

This webcast will introduce participants to deep learning techniques for microscopy image analysis. Three international experts will provide a short introduction to the foundations of deep learning for image analysis and then cover various methods for image denoising and restorations, super-resolution microscopy, label-free prediction, and cell/object detection. After the presentation, all speakers will be available for an extensive Q&A, giving the audience the chance to ask technical as well as application-specific questions. This webcast is mainly targeted to life scientists working with microscopy image data.

You will learn:
  • Foundations of deep learning for image analysis
  • Different applications of deep learning for image analysis
  • Answers to your specific questions in a live Q&A

This webcast has been produced for Nikon by Nature Research Custom Media. The sponsor retains sole responsibility for content. About this content.


Christophe Zimmer, Ph.D.
Research Director
Institut Pasteur, Paris, France
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Florian Jug, Ph.D.
Research Group Leader
Center for Systems Biology Dresden (CSBD), Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, and Fondazione Human Technopole, Milano, Italy
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Martin Weigert, Ph.D.
Group Leader
EPFL Lausanne
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Moderator: Sarah Hiddleston
Science Journalist
Nature Research for Nature Middle East
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