Stefan Stiller

7 papers receiving 264 citations

Stefan Stiller's Hit Papers

Ten deep learning techniques to address small data problems with remote sensing 2023 · 113 citations
1130+1+2Years since publication255075100

Peers

Stefan Stiller
Comparison fields: 5 of 94
  • Food Science 57
  • Health Informatics 3
  • Materials Chemistry 108
  • Organic Chemistry 61
  • Surfaces, Coatings and Films 12
Replace Zhanyi Wang with:
Zhanyi Wang China
Sibilla Orsini Italy
J. Henry United Kingdom
Jianhui Wu China
T. Jakubowski Poland
王辉 Wang Hui China
Junbo Zhang China
Joy Mazurek United States
Marko Peura Finland
Stefan Stiller relative to Zhanyi Wang China Zhanyi Wang's profile →
Citations per field
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Zhanyi Wang · 1×
Citations per year

Countries citing papers authored by Stefan Stiller

Since Specialization
Citations

This map shows the geographic impact of Stefan Stiller'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 Stefan Stiller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Stiller more than expected).

Fields of papers citing papers by Stefan Stiller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefan Stiller. 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 Stefan Stiller. The network helps show where Stefan Stiller may publish in the future.

Co-authors

The 22 scholars most cited alongside Stefan Stiller, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefan Stiller Line = papers co-authored together Stefan Stiller links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2003118
2
Ten deep learning techniques to address small data problems with remote sensing
Hit paper breakdown →
2023113
3 202210
4 20188
5 20248
6 20256
7 20244
8 20250

About Stefan Stiller

Stefan Stiller is a scholar working on Plant Science, Ecology, Artificial Intelligence, Ecological Modeling and Information Systems and Management, having authored 8 papers that have together received 267 indexed citations. Recurring topics across this work include Smart Agriculture and AI (3 papers), Remote Sensing in Agriculture (2 papers), Species Distribution and Climate Change (2 papers), Polymer Nanocomposite Synthesis and Irradiation (1 paper), Pickering emulsions and particle stabilization (1 paper), Plant Pathogens and Fungal Diseases (1 paper), Remote-Sensing Image Classification (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Food Science (57 citations), Health Informatics (3 citations), Materials Chemistry (108 citations), Organic Chemistry (61 citations) and Surfaces, Coatings and Films (12 citations). Stefan Stiller has collaborated with scholars based in Germany, China and Russia. Frequent co-authors include Masahiro Ryo, Gohar Ghazaryan, Anastasiia Safonova, Claas Nendel, Magdalena Main-Knorn, Rolf Daniels, Heiner Gers-Barlag, Jens Schulz, F. Pflücker and Klaus‐Peter Wittern. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, Biology Methods and Protocols, Polymer Composites, Colloids and Surfaces A Physicochemical and Engineering Aspects and Precision Agriculture.

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.

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