Mike Sips

1.1k citations
49 papers · 853 · h-index 16

Impact in

Papers in

Mike Sips

48 papers receiving 813 citations

Peers

Mike Sips
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 584
  • Signal Processing 248
  • Geography, Planning and Development 90
  • Computer Graphics and Computer-Aided Design 57
  • Ecological Modeling 41
Replace Jorge Poco with:
Jorge Poco Brazil
Sebastian Bremm Germany
Rick Walker United Kingdom
Mikael Jern Sweden
Chris Muelder United States
Masahiro Takatsuka Australia
Dong Hyun Jeong United States
Johannes Kehrer Norway
Harish Doraiswamy United States
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Mike Sips relative to Jorge Poco Brazil Jorge Poco's profile →
Citations per field
00.5×1.5×
Jorge Poco · 1×
Citations per year

Countries citing papers authored by Mike Sips

Since Specialization
Citations

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

Fields of papers citing papers by Mike Sips

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009162
2 200458
3 200447
4 200447
5 200642
6 201640
7 200539
8 201238
9 201233
10 200531
11 201630
12 200625
13 200423
14 201423
15 201522
16 201317
17 200315
18
FP-Viz: Visual Frequent Pattern Mining
200514
19 200614
20 200311

About Mike Sips

Mike Sips is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Geography, Planning and Development and Computer Networks and Communications, having authored 49 papers that have together received 853 indexed citations. Recurring topics across this work include Data Visualization and Analytics (35 papers), Data Management and Algorithms (14 papers), Time Series Analysis and Forecasting (8 papers), Geographic Information Systems Studies (7 papers), Video Analysis and Summarization (6 papers), Data Analysis with R (5 papers), Scientific Computing and Data Management (5 papers) and Species Distribution and Climate Change (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (584 citations), Signal Processing (248 citations), Geography, Planning and Development (90 citations), Computer Graphics and Computer-Aided Design (57 citations) and Ecological Modeling (41 citations). Mike Sips has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Daniel A. Keim, Christian Panse, Jörn Schneidewind, John Lewis, Pat Hanrahan, Boris Neubert, Stephen C. North, Doris Dransch, Norbert Marwan and Sungkil Lee. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Information Visualization, Computer Graphics Forum, Computers & Graphics and Cartography and Geographic Information Science.

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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