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Project 2: Detecting trypophobia triggers

Author: Piotr Migdał, PhD

Abstract: Trypophobia is a phobia of irregular patterns or clusters of small holes or bumps. It may arise from the sense of aversion towards skin infection with maggots or fungi. In general, this phenomenon is adaptive, because a strong sense of disgust may protect against touching infected humans, animals or corpses. Yet, it can also become maladaptive if some, otherwise benign, patterns cause a strong aversive response. During this workshop we will create an artificial convolutional neural network that predicts if an image is likely to cause a trypophobic response. Such networks are a state of the art technique for visual pattern detection.

The goal of the project is twofold:

We will provide the data for this project. The initial results are promising, see https://github.com/grzegorz225/trypophobia-detector

A list of 1-5 key papers/materials summarising the subject: 

In this case, only the basic knowledge of trypophobia is required. An additional knowledge may help with giving a general context, but most likely won’t contribute to the solution during this event:

https://en.wikipedia.org/wiki/Trypophobia

https://www.reddit.com/r/trypophobia/ (warning: triggers)

Additionally, take a look at:

Look at: http://p.migdal.pl/2017/04/30/teaching-deep-learning.html 

If you are new to Python, this book may be relevant: http://www.southampton.ac.uk/~fangohr/teaching/python/book.html 

A list of requirements for taking part in the project (education level / English level / programming language required): 

[a] BSc program, or higher 

[b] English: good, not necessarily proficient 

[c] programming languages / other competences: at least basics of Python (we will create a neural network in either Keras or PyTorch, modern frameworks for deep learning)

A maximal number of participants: 6 (1-2 per computer)

Skills and competences you can learn during the project: 

[a] practical experience with deep learning for image classification

[b] insights into how artificial neural networks abstract visual information processing

is there a plan for extending this work to a paper in case the results are promising? yes

Fig: The holes in lotus seed heads cause some anxiety in some people (source: Wikipedia)