[campus icon] Accesskey [ h ] University of Paderborn - Home
DE deutsch
Die Universität der Informationsgesellschaft
GET Lab LOGO

Theses and papers at the GET Lab

Overview of theses and papers at the GET Lab:

Below is a list of topics for theses which have been assigned in the GET Lab. The titles refer to the abstract of the respective work.

Legend:


Year:

Studienarbeiten:

finished Lukas Brinkmann (2019)
Vorverarbeitung natürlicher Kantenbilder zur echtzeitfähigen Objekterkennung

Masterarbeiten:

inprogress Mohammed Afroze (2019)
Detection of moving objects in dynamic environment
finished Sabarish Kumar Amaravadi (2019)
Enhancement of Real-Time Object Tracking Using Local Image Features
finished Hridkamol Biswas (2019)
Learning Condition-invariant Scene Representations for Across the Seasons Place Recognition
inprogress Christian Daube (2019)
Semantic Motion Segmentation using Deep Learning
inprogress Philip Frieling (2019)
Robust Odometry and Mapping at Low Computational Cost
inprogress Christopher Förster (2019)
Entwicklung und Vergleich von Methoden zur autonomen Navigation in unwegsamem Gelände für einen kettengetriebenen Roboter unter besonderer Berücksichtigung maschinellen Lernens
inprogress Satish Jai (2019)
Robot Grasping in Cluttered Environments
finished Ke Lu (2019)
Gesture-based Control System for a Robot Arm
inprogress Anshuman Nayak (2019)
Combining global-local features for robust appearance-based mapping
inprogress Sebastian Reinke (2019)
Real-Time Detection of Object Contours using Artificial Visual Attention
finished Mawe Sprenger (2019)
Convolutional Neural Network for Depth and Odometry Estimation from Monocular Video
finished Georg Stilow (2019)
Auswahl und Erweiterung eines lernbasierten Kantendetektionsverfahrens zur echtzeitfähigen Objekterkennung
inprogress Bashar Tomeh (2019)
Semantic Aware Lightweight Visual Place Recognition System for Severe Viewpoint and Appearance Variation
inprogress Sergej Wiebe (2019)
Korrespondenzbestimmung lokaler Bildmerkmale zur Objekterkennung unter Berücksichtigung geometrischer Informationen