Call for Participants: Identifying synthetic aerial images

post by Matthew Yates (2018 cohort)

Hello,

I am University of Nottingham 3rd year 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.

For this study I am looking for participants to take part in my ongoing online study on identifying synthetic aerial images. We have used Generative Adversarial Networks (GANs) to create these.

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.

This is study 2 in larger PhD project looking at the generation and detection of GAN synthesised earth observation data.

For more information on the project and studies please visit https://aiaerialimagery.wordpress.com/

 

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

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 consists of a short survey (2- 5 minutes) then a longer detection task (10-20 mins but can be completed in own time) hosted on Zooniverse.org. 

This study involves identifying the synthetic image out of a set of image pairs then marking the parts of the image that informed your decision.

How to participate? Read through the information on the project site and proceed to the link for Study 2

Project URL: https://aiaerialimagery.wordpress.com/   (See Study 2)

Study URL: https://formfaca.de/sm/_kBsk76eo

About the Zooniverse platform: https://www.zooniverse.org/lab

For any additional information or queries please feel free to contact me:
+44 (0) 747 386 1599     matthew.yates1@nottingham.ac.uk

Thanks for your time.

Matthew Yates

 

Detecting Fake Aerial Imagery – Call for participants

post by Matthew Yates (2018 cohort)

Hello everyone! I’m a 3rd year Horizon CDT PhD student partnered with the Defence Science and Technology Laboratory (Dstl). My PhD project is about the detection of deep learning generated aerial images, with the final goal of improving current detection models.

For this study, I am looking for participants to take part in my short online study on detecting fake aerial images. We have used Generative Adversarial Networks (GANs) to create these.

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

Purpose: To assess the difficulty in the task of distinguishing GAN-generated fake images from real aerial 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.

Link to study:  Detecting Fake Aerial Imagery

For any additional information or queries please feel free to contact me: matthew.yates1@nottingham.ac.uk

Thanks for your time,

Matthew Yates

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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