Ines Feldmann

1.2k citations
44 papers · 965 · h-index 18

Impact in

Papers in

Ines Feldmann

43 papers receiving 891 citations

Peers

Ines Feldmann
Comparison fields: 5 of 107
  • Analytical Chemistry 289
  • Spectroscopy 198
  • Computer Vision and Pattern Recognition 176
  • Geochemistry and Petrology 45
  • Computer Graphics and Computer-Aided Design 28
Replace Tatiana Trejos with:
Tatiana Trejos United States
Stefano Pagnotta Italy
Xiao Wu China
Giulia Lorenzetti Italy
Francesco Poggialini Italy
Janina Zięba‐Palus Poland
Fengxia Li China
Sofia Pessanha Portugal
Xu Zang China
Pavel Pořízka Czechia
Ines Feldmann relative to Tatiana Trejos United States Tatiana Trejos's profile →
Citations per field
00.5×1.7×
Tatiana Trejos · 1×
Citations per year

Countries citing papers authored by Ines Feldmann

Since Specialization
Citations

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

Fields of papers citing papers by Ines Feldmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ines Feldmann, 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 Ines Feldmann Line = papers co-authored together Ines Feldmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999135
2 199987
3 200267
4 199252
5 199251
6 200351
7 200947
8 202047
9 202238
10 200837
11 200735
12 202030
13 201629
14 201121
15 201921
16 201021
17 201720
18 200420
19 201618
20 202216

About Ines Feldmann

Ines Feldmann is a scholar working on Computer Vision and Pattern Recognition, Earth-Surface Processes, Computer Graphics and Computer-Aided Design, Media Technology and Analytical Chemistry, having authored 44 papers that have together received 965 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (12 papers), Building materials and conservation (6 papers), Mass Spectrometry Techniques and Applications (6 papers), Optical measurement and interference techniques (6 papers), Analytical chemistry methods development (5 papers), Computer Graphics and Visualization Techniques (4 papers), Image Processing Techniques and Applications (4 papers) and Chemical Synthesis and Characterization (3 papers). The work is most often cited by research in Analytical Chemistry (289 citations), Spectroscopy (198 citations), Computer Vision and Pattern Recognition (176 citations), Geochemistry and Petrology (45 citations) and Computer Graphics and Computer-Aided Design (28 citations). Ines Feldmann has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Norbert Jakubowski, Dietmar Stuewer, Peter P. Kauff, Oliver Schreer, Peter Eisert, Christoph Thomas, Joachim Koch, Kay Niemax, Ruben Gerrits and Nicole Atzpadin. Their work appears in journals such as Spectrochimica Acta Part B Atomic Spectroscopy, npj Materials Degradation, ChemistryOpen, Applied Sciences and Chemical Communications.

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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