Call for Participants: Detecting fake aerial images

PhD researcher Matthew Yates (2018 cohort) is currently recruiting participants to take part in a short online study on detecting fake aerial images. Generative Adversarial Networks (GANs) have been used to create these images.


Hello. I am 3rd year Horizon CDT PhD student partnered with the Dstl. My PhD project is about the detection of deep learning generated aerial images, with the final goal of improving current detection models.

I am looking for participants from all backgrounds, as well as those who have specific experience in dealing with either Earth Observation Data (Satellite aerial images) or GAN-generated images.

Purpose: To assess the difficulty in the task of distinguishing GAN generated fake images from real satellite photos of rural and urban environments.  This is part of a larger PhD project looking at the generation and detection of fake earth observation data.

Who can participate? This is open to anyone who would like to take part, although the involvement of people with experience dealing with related image data (e.g. satellite images, GAN images) is of particular interest.

Commitment: The study should take between 5-15 minutes to complete and is hosted online on pavlovia.org

How to participate? Read through this Information sheet and follow the link to the study at the end.

 Feel free to contact me with any queries.  Matthew.Yates1@nottingham.ac.uk

 

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