Jasper Linmans
Impact in
- Cell Biology top 10%
- Plant Pathogens and Fungal Diseases
Papers in
-
- AI in cancer detection 6
- Topic Modeling 1
-
- Generative Adversarial Networks and Image Synthesis 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- Martijn Rep (2 shared papers)Peter van Dam (1 shared paper)Sarah M. Schmidt (1 shared paper)Li‐Jun Ma (1 shared paper)Like Fokkens (1 shared paper)Harold Kistler (1 shared paper)Jeroen van der Laak (5 shared papers)Geert Litjens (4 shared papers)
- Journals
- Medical Image Analysis (2 papers)Fungal Genetics and Biology (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)Environmental Microbiology (1 paper)Laboratory Investigation (1 paper)
- Partner nations
- NetherlandsSwedenGermany
In The Last Decade
Jasper Linmans
9 papers receiving 289 citations
Peers
Comparison fields: 5 of 57
- Cell Biology 157
- Health Informatics 8
- Plant Science 171
- Biophysics 13
- Artificial Intelligence 58
Countries citing papers authored by Jasper Linmans
This map shows the geographic impact of Jasper Linmans'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 Jasper Linmans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jasper Linmans more than expected).
Fields of papers citing papers by Jasper Linmans
This network shows the impact of papers produced by Jasper Linmans. 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 Jasper Linmans. The network helps show where Jasper Linmans may publish in the future.
Co-authors
The 25 scholars most cited alongside Jasper Linmans, 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 | 2016 | 153 | |
| 2 | 2022 | 36 | |
| 3 | 2016 | 33 | |
| 4 | 2021 | 30 | |
| 5 | 2024 | 16 | |
| 6 | Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks | 2020 | 10 |
| 7 | Improved Semantic Segmentation for Histopathology using Rotation Equivariant Convolutional Networks | 2018 | 9 |
| 8 | 2018 | 2 | |
| 9 | 2023 | 1 |
About Jasper Linmans
Jasper Linmans is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cell Biology and Plant Science, having authored 9 papers that have together received 290 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Plant Pathogens and Fungal Diseases (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Mycorrhizal Fungi and Plant Interactions (2 papers), Digital Imaging for Blood Diseases (1 paper), Wikis in Education and Collaboration (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Cell Biology (157 citations), Health Informatics (8 citations), Plant Science (171 citations), Biophysics (13 citations) and Artificial Intelligence (58 citations). Jasper Linmans has collaborated with scholars based in Netherlands, Sweden and Germany. Frequent co-authors include Martijn Rep, Peter van Dam, Sarah M. Schmidt, Li‐Jun Ma, Like Fokkens, Harold Kistler, Jeroen van der Laak, Geert Litjens, Stefan Elfwing and Bas Beerens. Their work appears in journals such as Medical Image Analysis, Fungal Genetics and Biology, IEEE Journal of Biomedical and Health Informatics, Environmental Microbiology and Laboratory Investigation.
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.