David Zimmerer

Orcid: 0000-0002-8865-2171

According to our database1, David Zimmerer authored at least 33 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
CoRR, 2024

Visual Prompt Engineering for Medical Vision Language Models in Radiology.
CoRR, 2024

Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation.
CoRR, 2024

Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology.
CoRR, 2024

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024

Abstract: RecycleNet - Latent Feature Recycling Leads to Iterative Decision Refinement.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency.
CoRR, 2023

SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model.
CoRR, 2023

CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization.
CoRR, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023


Contrastive Representations for Unsupervised Anomaly Detection and Localization.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Unsupervised Learning for Anomaly Detection in Medical Images.
PhD thesis, 2022

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.
IEEE Trans. Medical Imaging, 2022

Unsupervised Anomaly Detection in the Wild.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Realistic Evaluation of FixMatch on Imbalanced Medical Image Classification Tasks.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data.
CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.
CoRR, 2021

GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Continuous-Time Deep Glioma Growth Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Abstract: Unsupervised Anomaly Localization Using Variational Auto-Encoders.
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019
A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients.
CoRR, 2019

High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection.
CoRR, 2019

Unsupervised Anomaly Localization Using Variational Auto-Encoders.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection.
CoRR, 2018

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.
CoRR, 2018

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
Int. J. Comput. Assist. Radiol. Surg., 2018

Advanced Deep Learning Methods.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
CoRR, 2017

Spiking Convolutional Deep Belief Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

2016
Robust environment perception for the Audi Autonomous Driving Cup.
Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016


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