Florian Jug
- Structural Biology top 1%
- Biophysics top 0.5%
- Cell Image Analysis Techniques 15
- Media Technology top 1%
- Image Processing Techniques and Applications 5
- Aging top 10%
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- Single-cell and spatial transcriptomics 6
- Genetics, Bioinformatics, and Biomedical Research 4
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- Scientific Computing and Data Management 4
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- Neural dynamics and brain function 4
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- Cellular Mechanics and Interactions 3
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- Tissue Engineering and Regenerative Medicine 2
- Co-authors
- Tim-Oliver BuchholzAlexander KrullPavel TomančákGaia PiginoAngelika StegerKevin W. EliceiriEllen T. A. DobsonCurtis Rueden
- Partner nations
- GermanyItalyUnited States
In The Last Decade
Florian Jug
37 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Structural Biology 145
- Biophysics 405
- Media Technology 332
- Computer Vision and Pattern Recognition 505
- Aging 28
Countries citing papers authored by Florian Jug
This map shows the geographic impact of Florian Jug's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Florian Jug with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Jug more than expected).
Fields of papers citing papers by Florian Jug
This network shows the impact of papers produced by Florian Jug. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Florian Jug. The network helps show where Florian Jug may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Florian Jug, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2024 | 22 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 8 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 3 | |
| 8 | 2022 | 27 | |
| 9 | 2021 | 50 | |
| 10 | 2020 | 176 | |
| 11 | DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders. | 2020 | 3 |
| 12 | 2020 | 57 | |
| 13 | 2020 | 53 | |
| 14 | 2019 | 89 | |
| 15 | Noise2Void - Learning Denoising From Single Noisy Imagesbreakdown → | 2019 | 709 |
| 16 | 2018 | 78 | |
| 17 | 2018 | 101 | |
| 18 | 2013 | 33 | |
| 19 | 2011 | 87 | |
| 20 | Automated quality assurance for UML models | 2005 | 1 |
About Florian Jug
Florian Jug is a scholar working on Biophysics, Structural Biology, Information Systems and Management, Media Technology and Aging, having authored 38 papers that have together received 2.1k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (15 papers), Single-cell and spatial transcriptomics (6 papers), Image Processing Techniques and Applications (5 papers), Scientific Computing and Data Management (4 papers), Neural dynamics and brain function (4 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Cellular Mechanics and Interactions (3 papers) and Tissue Engineering and Regenerative Medicine (2 papers). The work is most often cited by research in Structural Biology (145 citations), Biophysics (405 citations), Media Technology (332 citations), Computer Vision and Pattern Recognition (505 citations) and Aging (28 citations). Florian Jug has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Tim-Oliver Buchholz, Alexander Krull, Pavel Tomančák, Gaia Pigino, Angelika Steger, Kevin W. Eliceiri, Ellen T. A. Dobson, Curtis Rueden, Deborah Schmidt and Robert Haase. Their work appears in journals such as Current Biology, Nature Communications, Advanced Science, The Journal of Cell Biology and Nature Methods.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.