128 citations · 139 across the 5 of their papers we have counts for
5 papers
Token Cropr: Faster ViTs for Quite a Few Tasks
Benjamin Bergner, Christoph Lippert, Aravindh Mahendran
The adoption of Vision Transformers (ViTs) in resource-constrained applications necessitates improvements in inference throughput. To this end several token pruning and merging app…
Iterative Patch Selection for High-Resolution Image Recognition
Benjamin Bergner, Christoph Lippert, Aravindh Mahendran
High-resolution images are prevalent in various applications, such as autonomous driving and computer-aided diagnosis. However, training neural networks on such images is computati…
Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation
Josafat-Mattias Burmeister, Marcel Fernandez Rosas, Johannes Hagemann +5
Since labeling medical image data is a costly and labor-intensive process, active learning has gained much popularity in the medical image segmentation domain in recent years. A va…
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-rays
Benjamin Bergner, Csaba Rohrer, Aiham Taleb +6
We propose a simple and efficient image classification architecture based on deep multiple instance learning, and apply it to the challenging task of caries detection in dental rad…
3D Self-Supervised Methods for Medical Imaging
Aiham Taleb, Winfried Loetzsch, Noel Danz +4
Self-supervised learning methods have witnessed a recent surge of interest after proving successful in multiple application fields. In this work, we leverage these techniques, and…