Neuroinformatics Group

Universität BielefeldTechnische FakultätNI

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Sim4Dexterity

logoZiel des vom BMBF geförderten Verbundvorhabens Sim4Dexterity ist die Erzeugung synthetischer Daten für die Robotermanipulation mit hochwertigen, interaktiven und validierbaren Simulationswerkzeugen, so dass benötigte KI-Lösungen wirtschaftlich und zeiteffizient realisiert werden können.

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Robomantic - Tactile Sensors for Humans and Robots

Roboamtnic-title-imgEgo tango, ergo sum -> I feel, thus I am. This tenor brought the development of tactile sensitive devices within CITEC Bielefeld University to the next stage -> in terms of making the technology of skin-like touch sensors available to a wider public. With project funding by the EU and the state NRW - ERDF (EFRE), our team investigate in three development areas 1. Hardware, 2. Software and 3. Business, elaborating the basis for a stable university spin-off.

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Physical Reasoning Artificial Intelligence

 Try to solve the following physical puzzles to get an idea about this thesis / project: https://brainitongame.com  and  https://phyre.ai

We are developing an AI agent capable of solving such physical reasoning tasks. If you would like to know more about this thesis / project opportunity, please contact: 
Dr. Andrew Melnik <andrew.melnik(at)uni-bielefeld.de>

Abschluss: 
Bachelorarbeit
Abschluss: 
Master_Diplomarbeit
Ansprechpartner: 
anmelnik
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Deep Face Editing with StyleGAN

  Figure: animation of faces from old family photos using Deep Learning approaches

(source https://www.myheritage.com/deep-nostalgia)

This thesis / project will focus on practical applications of state of the art style generative adversarial network models (StyleGAN) [see References here].

If you would like to know more about this thesis / project opportunity, please contact: Dr. Andrew Melnik <andrew.melnik(at)uni-bielefeld.de>

Abschluss: 
Bachelorarbeit
Abschluss: 
Master_Diplomarbeit
Ansprechpartner: 
anmelnik
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Multi-agent dense traffic on complex railway networks

 This challenge tackles a key problem in the transportation world: How to efficiently manage dense traffic on complex railway networks? This is a real-world problem faced by many transportation and logistics companies around the world such as the Swiss Federal Railways and Deutsche Bahn. We are developing an AI agent capable of solving such problem

If you would like to know more about this thesis / project opportunity, please contact: 
Dr. Andrew Melnik <andrew.melnik(at)uni-bielefeld.de>
Abschluss: 
Bachelorarbeit
Abschluss: 
Master_Diplomarbeit
Ansprechpartner: 
anmelnik
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Deep Vision

 

Figure: Facebook AI [1]

 

This thesis / project will focus on practical applications of state of the art in computer vision [1][2] to detect objects and segment images [3][4][5][6]

[1] https://ai.facebook.com/blog/dino-paws-computer-vision-with-self-supervised-transformers-and-10x-more-efficient-training)

[2] https://www.youtube.com/watch?v=h3ij3F3cPIk&pp=qAMBugMGCgJkZRAB

[3] https://youtu.be/SfqN-Hc5two?t=612

[4] https://www.aicrowd.com/challenges/food-recognition-challenge

[5] https://www.aicrowd.com/challenges/global-wheat-challenge-2021

[6https://youtu.be/HS1wV9NMLr8

 

If you would like to know more about this thesis / project opportunity, please contact: Dr. Andrew Melnik <andrew.melnik(at)uni-bielefeld.de>

Abschluss: 
Bachelorarbeit
Abschluss: 
Master_Diplomarbeit
Ansprechpartner: 
anmelnik
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