Jan Pirklbauer

According to our database1, Jan Pirklbauer authored at least 12 papers between 2020 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
A detailed library perspective on nearly unsupervised information extraction workflows in digital libraries.
Int. J. Digit. Libr., June, 2024

A discovery system for narrative query graphs: entity-interaction-aware document retrieval.
Int. J. Digit. Libr., March, 2024

URGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement.
CoRR, 2024

URGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement.
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024

Employing Real Training Data for Deep Noise Suppression.
Proceedings of the IEEE International Conference on Acoustics, 2024

On Camera and LiDAR Positions in End-to-End Autonomous Driving.
Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023
A Super-Resolution Training Paradigm Based on Low-Resolution Data Only to Surpass the Technical Limits of STEM and STM Microscopy.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
A library perspective on nearly-unsupervised information extraction workflows in digital libraries.
Proceedings of the JCDL '22: The ACM/IEEE Joint Conference on Digital Libraries in 2022, Cologne, Germany, June 20, 2022

What a publication tells you: benefits of narrative information access in digital libraries.
Proceedings of the JCDL '22: The ACM/IEEE Joint Conference on Digital Libraries in 2022, Cologne, Germany, June 20, 2022

2021
A Toolbox for the Nearly-Unsupervised Construction of Digital Library Knowledge Graphs.
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2021

Narrative Query Graphs for Entity-Interaction-Aware Document Retrieval.
Proceedings of the Towards Open and Trustworthy Digital Societies, 2021

2020
A Semantically Enriched Dataset based on Biomedical NER for the COVID19 Open Research Dataset Challenge.
CoRR, 2020


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