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Open thesis topics

There are currently no open thesis topics. If you are interested, please contact us.

Previous Theses

• master
  Jacob Schwaß
  Multi-Backbone Embedding-Fusion: An Attention-Based Deep Learning Approach for Fusing Heterogeneous Computer Vision Backbones
  Abstract
• master
  Mirko Lehn
  Developing a Domain-Specific Foundation Model with Adapters and Self-Supervised Learning for Efficient Plant Detection in Grasslands
  Abstract
• master
  Sebastian Reuter
  Semantic Interoperability in the Web of Things: Design and Validation of a Reference Data Model for Monitoring Applications in the Grasslands Agricultural Domain
  Abstract
• master
  Dennis Vaupel
  Generation of Synthetic Training Data for Neural Network based Weed Detection with Stable Diffusion
  Abstract
• master
  Renke Hohl
  Deep Learning based Growth Modeling of Plant Phenotypes
  Abstract
• bachelor
  Till Koch
  Generation of Synthetic Model-Based Image Data for Training Artificial Neural Networks
  Abstract
• Bachelor
  Nico Soethe
  Evaluation and Selection of an Object Detection Model for Weed Detection in Grassland
  Abstract