Scholar
Lukas Knobel
Google Scholar ID: egwx6IMAAAAJ
Fundamental AI Lab, University of Technology Nuremberg
Citations & Impact
Citations
14
H-index
2
i10-index
1
Publications
4
Co-authors
0
Resume (English only)
Academic Achievements
- 1. Paper “Learning to Count without Annotations” accepted at CVPR2024
- 2. Paper “Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks” presented at ICCV 2023 - Visual Inductive Priors for Data-Efficient Deep Learning Workshop
Research Experience
- 1. Machine Learning Scientist at TNO's Intelligent Imaging group
- 2. PhD candidate in the Fundamental AI Lab at the University of Technology Nuremberg
Education
- 1. MSc in Artificial Intelligence, University of Amsterdam
- 2. Bachelor’s in Computer Engineering, completed in collaboration with Airbus
- 3. ELLIS PhD candidate, University of Technology Nuremberg, supervised by Yuki Asano, co-supervised by Andrew Zisserman (University of Oxford)
Background
- ELLIS PhD candidate, with research interests in self-supervised learning and multimodal foundation models.
Co-authors