• Current Bachelor Students

    • Martin Kolaczek
    • Julius Maetzig

  • Current Master Students

    • Florian Fechner
    • Valentin Brosch
    • Sufian Zaabalawi
    • Daniel Beckmann
    • Leon Pielage
    • Joschka Strüber
    • David Pracht
    • Jonathan Wandscheer
    • Henning Janßen
    • Clemens Kohl
    • Timm Jasper Kühnel
    • Yannik Berndsen
    • Christoph Friedrich

  • Finished Bachelor Theses

    • Viktor Gorte: Comparing Closed and Open Source SfM Pipelines to Reconstruct Natural Environments
    • Raoul Kanschat: Efficient Key-Frame selection and Panorama Stitching for Geospatial Visual Animal Tracking
    • Jan Phillip Bläs: Entropy as a Measure to Quantify the Training Quality of Neural Networks
    • Gabriela Cristina Feldhaus: Quantifying the Cyclic ICG-Flow in Angiography Videos
    • Clemens Kohl: Resolving Collisions of Visually Indistinguishable Objects using Fully Convolutional Networks
    • Allan Grunert: Optical Flow-based Detection of Small Objects in Cluttered Environments
    • Jacomo Axel Krause: Advanced Support and Infill Generation for Additive Manufacturing
    • Jacqueline Kockwelp: Evaluating Different Deep Learning Architectures To Resolve Colliding Drosophila Melanogaster Larvae
    • Timm Jasper Kühnel: An Empirical Study of Critical Configurations in Monocular Structure-from-Motion
    • Anatoli Dick: Compensating Unbalanced Data using Style Transfer for Machine Learning-based Camera Trap Image Classification
    • Julitta Sucker: Towards Parameter-free Deep Learning in Biomedical Applications - Evaluating Multiple Early Stopping Criteria for Image Segmentation

  • Finished Master Theses

    • Lars Haalck: Approaching Critical Configurations in Monocular Structure-from-Motion for In-Field Animal Tracking
    • Frederik Probst: CNN-based Animal Classification in a Novel Camera Trap Database
    • Christian Lentfort: Laser Light Plane Based Motion Analysis: Construction of a Prototype
    • Christof Duhme: Deep learning-based Blood Vessel Segmentation in Neurosurgical Angiography Recordings
    • Thomas Teodorowicz: Random Forest-based Active Learning for Angiographic Image Segmentation
    • Christian Wollny: Uncertainty Sample-based Active Learning Through Associative Reinforcement Learning
    • Julian Hesse: Learning to See in the Noise - Deep Learning-based Image Restoration of Short Exposure EM Images
    • Karim Huesmann: Real-time Layer-wise Analysis of Convolutional Neural Networks
    • Sebastian Thiele: Capsules Only Look Once - Comparing State-of-the-Art Deep Learning Architectures in a Novel Coats of Arms Image Domain
    • Christoph Blecke: CamGanAPI: A Modular Camera Gantry Programming Interface for Reactive Additive Manufacturing
    • Dominik Berse: Machine Learning for Additive Manufacturing: Analysing Multiple Accelerometer Readings for 3D Printing
    • Eike Gebauer: Real-time Monitoring of 3D Printers: Machine Learning Based Anomaly Detection by Monitoring the Load of Multiple Stepper Motors
    • Mareen Hoffmann: Automatic Analysis of Sperm Mobility for Reproductive Medicine - Comparing a Deterministic and a Probabilistic Tracking Approach for Small Objects Under the Consideration of Drift
    • Marvin Stuffert: Possibilities and Limitations of a Real-Time Insect Camera Trap
    • Pascal Kockwelp: Machine Learning Meets Polarisation: Approximating Polarised Light Properties based on Static RGB Images using Fully Convolutional Neural Networks
    • Bafrin Krad: Analysis of Age-related Macular Degeneration in OCT Images with Deep Convolutional Neural Networks
    • Daniel Müller: Considerate Additive Manufacturing: A Machine Learning-based Closed-Loop Skin Detection and Collision Avoidance System for 3D Printing
    • Hans-Christian Lindner: Developing a robotic lawn mower using a convolutional neural network for object detection with an external camera and different SLAM algorithms for navigation
    • André Machate: Evaluation of deterministic and probabilistic deep learning models to improve short exposed electron microscope images
    • Julian Bigge: Hatching-Box: Monitoring the Rearing Process of Drosophila Using an Embedded Imaging and in-Vial Detection System
    • Leonard Allewelt: Automatic analysis of sperm movement and roll behavior using Deep Neural Networks
    • Jacqueline Kockwelp: Deep Learning-based Analysis of High Resolution Cytological Imagery for AML Prognosis
    • Jan Ewald: Machine learning-based forensic analysis of images and videos for deepfake detection