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            • Theses Supervision | Prof. Dr. Fabian Gieseke
 
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Prof. Dr. Fabian Gieseke
Professor

Data Science: Machine Learning and Data Engineering

Leonardo Campus 3
48149 Münster


Room: 233

Phone: +49 251 83-38151
fabian.gieseke@wi.uni-muenster.de

ShortURL: ERC.IS ShortURL erc.is/p/fabian.gieseke

  • About
  • Publications
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  • Courses
  • Theses Supervision
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  • Supervised Theses

    • Semi-Supervised Machine Learning for Query By Example on Relational Databases (Master's thesis IS, 2022)
    • Collecting personal learner information in digital education: From tedious questionnaire to entertaining chatbot experience (Master's thesis IS, 2022)
    • Web tracking and its application for Learning Analytics: A case study with reveal.js (Master's thesis IS, 2022)
    • Jan Pauls: Generating High-Resolution Height Maps Using Deep Neural Networks (Master's thesis IS, 2022)
    • Linus Stach: Application of Transferable Adversarial Attacks on Convolutional Neuronal Networks: An Evaluation of Existing Attack and Defense Mechanisms (Bachelor's thesis IS, 2022)
    • Detection and Segmentation of Tree Instances on a Rwandan Satellite Dataset (Bachelor's thesis IS, 2022)
    • Customer Behavior Predictions for Online Travel Agencies: A Practical Implementation (Master's thesis IS, 2022)
    • Data provenance for a semantically-structured representation of license information for open educational resources (Bachelor's thesis IS, 2022)
    • Erik Zimmermann: Development of a gradient-free adversarial attack on convolutional neural networks to evaluate existing defense strategies. (Bachelor's thesis IS, 2022)
    • Deep Learning Semantic Segmentation of Tree Stock in South Africa Using Satellite Images (Bachelor's thesis IS, 2022)
    • Experimental Improvement of Streaming Quality in a Cloud-Based Geographical Information System (Bachelor's thesis IS, 2022)
    • Machine Learning Under Resource Limitations (Bachelor's thesis IS, 2021)
    • Efficient Convolutional Neural Network Inference on Microcontrollers (Bachelor's thesis IS, 2021)
    • Reverse image search using deep discrete feature extraction and locality-sensitive hashing (Bachelor's thesis IS, 2021)
    • Thomas Ackermann: Investigating Deep Learning-based Strategies to Cope with Label Noise in Satellite Data Using the Example of African Non-Forest Trees (Master's thesis IS, 2021)
    • Semantic Segmentation of Satellite Images Using Point Supervision (Master's thesis IS, 2021)
    • Investigating the Practicability of Deep Learning based Super- and Upsampling Approaches for Satellite Data (Bachelor's thesis IS, 2021)
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Contact

Data Science: Machine Learning and Data Engineering
Prof. Dr. Fabian Gieseke

Leonardo-Campus 3
48149 Münster
Deutschland

Tel.: +49 251 83-38150
Fax: +49 251 83-38159
sek-dasc@wi.uni-muenster.de

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