Search Results for author:
Found 7 papers, 5 papers with code
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding
We investigate the combination of encoder-decoder LLMs with both encoder-decoder and decoder-only SLMs from different model families and only require fine-tuning of the SLM.
Iterative Patch Selection for High-Resolution Image Recognition
We propose a simple method, Iterative Patch Selection (IPS), which decouples the memory usage from the input size and thus enables the processing of arbitrarily large images under tight hardware constraints.
Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation
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.
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-rays
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 radiographs.
The Regularizing Effect of Different Output Layer Designs in Deep Neural Networks
Deep neural networks are prone to overfitting, especially on small datasets.
3D Self-Supervised Methods for Medical Imaging
Self-supervised learning methods have witnessed a recent surge of interest after proving successful in multiple application fields.
HPI-DHC at TREC 2018 Precision Medicine Track
The TREC-PM challenge aims for advances in the field of information retrieval applied to precision medicine.
Ranked #1 on
Information Retrieval
on TREC-PM
