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Deep learning for image analysis – Course and Conference Office

EMBL Course

Deep learning for image analysis

Overview

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.

Registration is not yet open for this event. If you are interested in receiving more information please register your interest.

Course overview

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.

Audience

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.

Learning outcomes

After this course you should be able to:

  • Understand the fundamentals of machine learning methods suitable for image analysis
  • Advise users/colleagues in strategies to obtain ground truth
  • Train and use a CNN for a bioimage analysis task studied in the course
  • Perform simple quality control on the results

What past participants say about the course

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

Sponsors

Sponsorship opportunities

We offer a variety of event sponsoring possibilities, with the flexibility to select a set sponsorship package or combine individual sponsorship options to suit your event budget. Discounts are available for companies sponsoring multiple events at EMBL Heidelberg. View other events, or contact sponsorship@embl.de for further information.

If you are interested in becoming a media partner of this event, please visit our media partnerships webpage.

Warning

EMBL wishes to warn sponsors of EMBL conferences and courses of fraudulent schemes purporting to offer sponsorship opportunities on behalf of EMBL or affiliated with EMBL officials. One current scam campaign of which we are aware is conducted using the name ‘Judy Eastman’ (judy@gopcontact.a2hosted.com) and entails approaches to sponsors offering sponsorship opportunities on EMBL’s behalf. Please be kindly advised that all relevant communication regarding sponsorship of EMBL conferences, symposia and courses is handled by EMBL directly and is sent from an official EMBL account. EMBL does not work with any external providers on sponsorship acquisition.

Please also note that:

  • EMBL never provides attendee lists for purchase. Any offers of such are fraudulent.
  • EMBL will never call or email you to ask for your credit card details or to request a payment.
  • All payments are on invoice.

Suspicious communications purportedly from, for or on behalf of EMBL should be reported to EMBL at the following email address sponsoring@embl.de.

Date: 5 - 9 Jun 2023

Location: EMBL Heidelberg

Venue: EMBL Advanced Training Centre


EMBL Courses and Conferences are kindly supported by our Corporate Partnership Programme

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