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F. Nensa

4 papers hereh-index 395.4k citations197 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CL1
  • cs.CV1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2025

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries

Frederic Jonske, Moon Kim, Enrico Nasca +8

It is an open secret that ImageNet is treated as the panacea of pretraining. Particularly in medical machine learning, models not trained from scratch are often finetuned based on…

eess.IV2024

SALT: Introducing a Framework for Hierarchical Segmentations in Medical Imaging using Softmax for Arbitrary Label Trees

Sven Koitka, Giulia Baldini, Cynthia S. Schmidt +11

Traditional segmentation networks approach anatomical structures as standalone elements, overlooking the intrinsic hierarchical connections among them. This study introduces Softma…

eess.IV2024

ROCOv2: Radiology Objects in COntext Version 2, an Updated Multimodal Image Dataset

Johannes Rückert, Louise Bloch, Raphael Brüngel +11

Automated medical image analysis systems often require large amounts of training data with high quality labels, which are difficult and time consuming to generate. This paper intro…

cs.CL2024

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding

Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17

Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…

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