Summer School on Image Analysis for Plant Phenotyping

Summer School

Summer School on Image Analysis for Plant Phenotyping

Are you looking for a complete overview of image analysis techniques for automatic plant phenotyping? The course will provide a mixture of underlying theory and practical hands-on training. During the course you will have the opportunity to work on real plant image analysis problems so you can apply it directly in practice.

Organised by Wageningen Academy

Mon 29 June 2020 until Fri 3 July 2020

Duration 5 days
Location Wageningen Campus

This Summer School is scheduled, but not open yet for registration. Show your interest to stay informed:

Practical information
Price indication € 2495.- for industry / € 1495.- for PhD
Min/Max participants 15 - 35
Rating 4.5 (scale 1 to 5)

Programme and topics

In this programme, a mixture of lectures from experts from Wageningen University & Research and leading international experts in this domain, in the field, are combined with hands-on training. During the Summer
School there is ample time to discuss the issues of importance to your company/institutions with the experts. We will pay attention to the following subjects:
- Image acquistion
- Noise filtering
- Segmentation and image shape features
- Machine learning
- Deep learning
- 3D vision
- Imaging, data and practicals

    Target group

    This Summer School is primarily intended for researchers working on automatic phenotyping and technical experts in breeding companies who use, or plan to use, image analysis. If you have doubts whether you belong to the target group or have enough relevant basic knowledge,
    please don’t hesitate to contact us.


    After following this Summer School you know about the latest insights in imaging techniques applied to plant phenotyping. Furthermore, you will be able to apply it in daily practice in your experiments.

    Course leaders

    The Summer School is given by dr. Gerrit Polder, dr. Gert Kootstra and Rick van de Zedde MSc, Wageningen University & Research.

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