Daniel Schmitter
Impact in
- Endocrine and Autonomic Systems top 10%
- Circadian rhythm and melatonin
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- Computer Graphics and Visualization Techniques 4
-
- Medical Image Segmentation Techniques 5
- Image and Object Detection Techniques 2
- Co-authors
- Michaël UnserDaniel SageRicard Delgado-GonzaloVirginie UhlmannMarlen KnoblochMarta RoccioMatthias P. LütolfMeritxell Bach Cuadra
- Journals
- IEEE Signal Processing Letters (4 papers)IEEE Transactions on Image Processing (3 papers)NeuroImage Clinical (2 papers)BioScience (1 paper)Computational Visual Media (1 paper)
- Partner nations
- SwitzerlandGermanyItaly
In The Last Decade
Daniel Schmitter
23 papers receiving 533 citations
Peers
Comparison fields: 5 of 103
- Endocrine and Autonomic Systems 65
- Biophysics 55
- Aging 13
- Computer Graphics and Computer-Aided Design 21
- Developmental Neuroscience 23
Countries citing papers authored by Daniel Schmitter
This map shows the geographic impact of Daniel Schmitter'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 Daniel Schmitter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Schmitter more than expected).
Fields of papers citing papers by Daniel Schmitter
This network shows the impact of papers produced by Daniel Schmitter. 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 Daniel Schmitter. The network helps show where Daniel Schmitter may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Schmitter, 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 | 2025 | 2 | |
| 2 | 2020 | 5 | |
| 3 | 2017 | 2 | |
| 4 | 2017 | 4 | |
| 5 | 2017 | 16 | |
| 6 | 2016 | 6 | |
| 7 | 2016 | 17 | |
| 8 | 2016 | 2 | |
| 9 | 2015 | 20 | |
| 10 | 2015 | 6 | |
| 11 | 2015 | 2 | |
| 12 | 2015 | 14 | |
| 13 | 2015 | 2 | |
| 14 | 2015 | 6 | |
| 15 | 2014 | 154 | |
| 16 | 2014 | 11 | |
| 17 | 2014 | 50 | |
| 18 | 2013 | 12 | |
| 19 | 2013 | 81 | |
| 20 | 2012 | 117 |
About Daniel Schmitter
Daniel Schmitter is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Computational Mechanics, Biophysics and Developmental Neuroscience, having authored 23 papers that have together received 539 indexed citations. Recurring topics across this work include Advanced Numerical Analysis Techniques (11 papers), 3D Shape Modeling and Analysis (6 papers), Medical Image Segmentation Techniques (5 papers), Computer Graphics and Visualization Techniques (4 papers), Cell Image Analysis Techniques (3 papers), AI in cancer detection (2 papers), Microtubule and mitosis dynamics (2 papers) and Image and Object Detection Techniques (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (65 citations), Biophysics (55 citations), Aging (13 citations), Computer Graphics and Computer-Aided Design (21 citations) and Developmental Neuroscience (23 citations). Daniel Schmitter has collaborated with scholars based in Switzerland, Germany and Italy. Frequent co-authors include Michaël Unser, Daniel Sage, Ricard Delgado-Gonzalo, Virginie Uhlmann, Marlen Knobloch, Marta Roccio, Matthias P. Lütolf, Meritxell Bach Cuadra, Alessandro Daducci and Alexis Roche. Their work appears in journals such as IEEE Signal Processing Letters, IEEE Transactions on Image Processing, NeuroImage Clinical, BioScience and Computational Visual Media.
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.