Michael Neff

3.0k citations
74 papers · 1.6k · h-index 24

Impact in

Papers in

Michael Neff

70 papers receiving 1.6k citations

Peers

Michael Neff
Comparison fields: 5 of 117
  • Human-Computer Interaction 521
  • Computer Vision and Pattern Recognition 638
  • Control and Systems Engineering 594
  • Computer Graphics and Computer-Aided Design 67
  • Computational Mathematics 10
Replace Satoshi Matsuoka with:
Satoshi Matsuoka Japan
Jean‐Marie Normand France
Bernd Fröhlich Germany
Francisco J. Perales Spain
Josh Tenenbaum United States
T. Okoshi Japan
Eric L. Schwartz United States
András Lörincz Hungary
Stefan Brückner Norway
Dominik Endres Germany
Michael Neff relative to Satoshi Matsuoka Japan Satoshi Matsuoka's profile →
Citations per field
00.5×10×
Satoshi Matsuoka · 1×
Citations per year

Countries citing papers authored by Michael Neff

Since Specialization
Citations

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

Fields of papers citing papers by Michael Neff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018184
2 2009176
3 2008133
4 199959
5 201157
6 201556
7 201952
8 200749
9 200245
10 202142
11 201939
12 202338
13 202238
14 201737
15 202130
16 201630
17 201229
18 201327
19 200526
20 202026

About Michael Neff

Michael Neff is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction, Social Psychology and Experimental and Cognitive Psychology, having authored 74 papers that have together received 1.6k indexed citations. Recurring topics across this work include Human Motion and Animation (41 papers), Human Pose and Action Recognition (28 papers), Hand Gesture Recognition Systems (17 papers), Video Analysis and Summarization (14 papers), Action Observation and Synchronization (8 papers), Virtual Reality Applications and Impacts (7 papers), Music Technology and Sound Studies (5 papers) and Advanced Chemical Physics Studies (5 papers). The work is most often cited by research in Human-Computer Interaction (521 citations), Computer Vision and Pattern Recognition (638 citations), Control and Systems Engineering (594 citations), Computer Graphics and Computer-Aided Design (67 citations) and Computational Mathematics (10 citations). Michael Neff has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Guntram Rauhut, Eugene Fiume, Irene Albrecht, Michael Kipp, Yingying Wang, Hans‐Peter Seidel, Ylva Ferstl, Rachel McDonnell, Marilyn Walker and Victor Zordan. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum, ACM Transactions on Applied Perception, Language Resources and Evaluation and Leonardo.

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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