Proof of COVID-19 vaccination or recovery is required to attend this on-site course. Please see EMBL’s COVID-19 safety policy for on-site events.
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The advent of deep learning has brought a revolution in the field of computer vision, including most tasks and research questions concerned with microscopy image analysis. Neural networks have been successfully used for image restoration, classification and segmentation, for the detection of objects and characterisation of their morphology, for high-throughput imaging and large-scale processing in 3D. Despite these advances, training and deployment of such neural networks remains difficult for practitioners of image analysis. The aim of our course is to close this gap and teach the participants – in the most hands-on way possible – to apply deep learning-based methods to their own data and image analysis problems.
This course is aimed at both core facility staff and research scientists.
Prerequisites for this workshop are programming skills in Python and ideally Tensorflow, Keras or Pytorch as well as basic knowledge of machine learning theory.
After this course you should be able to:
“I enjoyed every single day of this course: not only have I learned so much on how to approach an image analysis problem using Deep Learning, but also I had a great great great time coding and discussing with the other participants and the instructors!” – Lucrezia Ferme, Instituto Gulbenkian de Ciência, Portugal
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