Tim Lammarsch
-
- Data Visualization and Analytics 16
- Video Analysis and Summarization 5
- Signal Processing top 10%
- Time Series Analysis and Forecasting 7
- Data Management and Algorithms 5
-
- Species Distribution and Climate Change 2
- Artificial Intelligence top 10%
- Anomaly Detection Techniques and Applications 2
-
- Multimedia Communication and Technology 5
-
- Geographic Information Systems Studies 2
- Co-authors
- Silvia MikschWolfgang AignerAlexander RindPeter FilzmoserMarkus WagnerJohannes GärtnerMichael SmucEva Mayr
- Journals
- IEEE Transactions on Visualization and Computer Graphics (2 papers)Computer Graphics Forum (2 papers)Computers & Graphics (1 paper)
- Partner nations
- AustriaGermanyUnited Kingdom
In The Last Decade
Tim Lammarsch
17 papers receiving 265 citations
Peers
Comparison fields: 5 of 62
- Computer Vision and Pattern Recognition 238
- Signal Processing 72
- Ecological Modeling 16
- Human-Computer Interaction 17
- Artificial Intelligence 94
Countries citing papers authored by Tim Lammarsch
This map shows the geographic impact of Tim Lammarsch'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 Tim Lammarsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Lammarsch more than expected).
Fields of papers citing papers by Tim Lammarsch
This network shows the impact of papers produced by Tim Lammarsch. 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 Tim Lammarsch. The network helps show where Tim Lammarsch may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Tim Lammarsch, 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 | 2018 | 51 | |
| 2 | 2017 | 11 | |
| 3 | 2016 | 9 | |
| 4 | 2015 | 40 | |
| 5 | 2015 | 4 | |
| 6 | 2015 | 12 | |
| 7 | 2014 | 4 | |
| 8 | 2013 | 20 | |
| 9 | 2013 | 40 | |
| 10 | 2013 | 8 | |
| 11 | 2013 | 2 | |
| 12 | 2012 | 5 | |
| 13 | 2011 | 8 | |
| 14 | 2010 | 1 | |
| 15 | 2009 | 28 | |
| 16 | 2009 | 27 | |
| 17 | 2008 | 9 |
About Tim Lammarsch
Tim Lammarsch is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Ecological Modeling, Geography, Planning and Development and Human-Computer Interaction, having authored 17 papers that have together received 279 indexed citations. Recurring topics across this work include Data Visualization and Analytics (16 papers), Time Series Analysis and Forecasting (7 papers), Video Analysis and Summarization (5 papers), Data Management and Algorithms (5 papers), Multimedia Communication and Technology (5 papers), Anomaly Detection Techniques and Applications (2 papers), Geographic Information Systems Studies (2 papers) and Species Distribution and Climate Change (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (238 citations), Signal Processing (72 citations), Ecological Modeling (16 citations), Human-Computer Interaction (17 citations) and Artificial Intelligence (94 citations). Tim Lammarsch has collaborated with scholars based in Austria, Germany and United Kingdom. Frequent co-authors include Silvia Miksch, Wolfgang Aigner, Alexander Rind, Peter Filzmoser, Markus Wagner, Johannes Gärtner, Michael Smuc, Eva Mayr, Gennady Andrienko and Daniel A. Keim. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computers & Graphics, IEEE Computer Graphics and Applications and Information Visualization.
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.