Niklas Penzel
Zitiert von
Zitiert von
Conditional dependence tests reveal the usage of ABCD rule features and bias variables in automatic skin lesion classification
C Reimers, N Penzel, P Bodesheim, J Runge, J Denzler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Investigating neural network training on a feature level using conditional independence
N Penzel, C Reimers, P Bodesheim, J Denzler
European Conference on Computer Vision, 383-399, 2022
Analyzing the Behavior of Cauliflower Harvest-Readiness Models by Investigating Feature Relevances
N Penzel, J Kierdorf, R Roscher, J Denzler
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW …, 2023
Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization
J Blunk, N Penzel, P Bodesheim, J Denzler
When Medical Imaging Met Self-Attention: A Love Story That Didn't Quite Work Out
T Piater, N Penzel, G Stein, J Denzler
arXiv preprint arXiv:2404.12295, 2024
Reducing Bias in Pre-trained Models by Tuning while Penalizing Change
N Penzel, G Stein, J Denzler
arXiv preprint arXiv:2404.12292, 2024
The Power of Properties: Uncovering the Influential Factors in Emotion Classification
T Büchner, N Penzel, O Guntinas-Lichius, J Denzler
arXiv preprint arXiv:2404.07867, 2024
Interpreting Art by Leveraging Pre-Trained Models
N Penzel, J Denzler
2023 18th International Conference on Machine Vision and Applications (MVA), 1-6, 2023
Investigating the Consistency of Uncertainty Sampling in Deep Active Learning
N Penzel, C Reimers, CA Brust, J Denzler
DAGM GCPR 2021 43, 159-173, 2021
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