Abschlussarbeiten

Hinweise zu Abschlussarbeiten

Bitte lesen Sie diese Hinweise, bevor Sie uns kontaktieren.
Abschlussarbeiten umfassen Bachelor-, Diplom-, Master- und Studienarbeiten.
Für eine Initiativbewerbung füllen Sie den Bewerber-Fragebogen aus und senden Sie ihn zusammen mit einem tabellarischen Lebenslauf und einem aktuellen Notenauszug an M.Sc. Nils Rack.

Zu vergebende Themen
Titel	Betreuer
Deep Learning: Mapshift-Prediction based on (deprecated) map priors for online map perception (deutsch/english)	M.Sc. Jonas Merkert
Deep Learning + Software Engineering: Effect of noisy map labels on the map perception task	M.Sc. Jonas Merkert
Visiting Master's Thesis @ University of Alberta, Canada	Prof. Dr. Ehsan Hashemi
Evaluierung und Integration von Nvidia Omniverse in einem CARLA-basierten Simulationsframework	M.Sc. Kaiwen Wang
Machine Learning for Decision-Making in Autonomous Driving	M.Sc. Nick Le Large
Leveraging Large Language Models for Decision-Making in Autonomous Driving	M.Sc. Nick Le Large
Integrating State-of-the-Art Motion Planning Algorithms into Decision-Making for Autonomous Driving	M.Sc. Nick Le Large
Latent Scene Generation	M.Sc. Marlon Steiner
Algorithmen + Deep Learning: Traffic Light to Lane Assignment für die Offline Anwendung in der Autolabeling Cloud (deutsch/english)	M.Sc. Richard Fehler
Deep Learning & Software Engineering: Classification or Detection of Polylines with Aerial Images as CNN Input (deutsch/english)	M.Sc. Richard Fehler
Applied Deep Learning: Training and Evaluation of a Large Panoptic Segmentation Neural Network Model on the Mapillary Vistas 2 Dataset (deutsch/english)	M.Sc. Richard Fehler
Deep Learning and Mapping: Parametric Mapping on Argoverse2 Dataset with Deep Neural Networks and 3D Mapping (deutsch/english)	M.Sc. Richard Fehler
Deep Learning: Consistent BEV Map Perception with Spatiotemporal NeuralMemoryBuffer for GlobalMap Perception (deutsch/english)	M.Sc. Richard Fehler
Deep Learning: Long Range BEV Map Perception with: Virtual Telephoto Camera / Lidar Sensor Fusion / SD Map Priors (deutsch/english)	M.Sc. Richard Fehler
Deep Learning: Shared ResNet50 Backbone for Mask2Former and MapTRv2 (like Tesla HydraNet) (deutsch/english)	M.Sc. Richard Fehler
Applied Deep Learning & Software Engineering: Map Perception Extended to Bicycle Lanes (deutsch/english)	M.Sc. Richard Fehler
Software Engineering: Optimal Graph Splitting and Merging of OpenStreetMap Road Networks for Highly ParallelHD-MappingforDeepLearning in Autonomous Driving (deutsch/english)	M.Sc. Richard Fehler
Augmentation Methods for Birds-Eye-View Road Feature Perception with Deep Learning	M.Sc. Fabian Immel
Logical Consistency for Birds-Eye-View Road Feature Perception with Deep Learning	M.Sc. Fabian Immel
Modeling Uncertainty for Birds-Eye-View Map Perception with Detection Transformers	M.Sc. Fabian Immel
Traffic Light to Lane Association for Online Road Feature Perception with Deep Learning	M.Sc. Fabian Immel