Anita Graser

66 papers receiving 1.4k citations

Hit Papers

Convolutional Neural Networks for P300 Detection with App...20102026201520202010100200300400500

Peers

Anita Graser
Comparison fields: 5 of 118
  • Cognitive Neuroscience 623
  • Electrical and Electronic Engineering 274
  • Cellular and Molecular Neuroscience 252
  • Signal Processing 249
  • Computer Vision and Pattern Recognition 192
Replace Sarath Kodagoda with:
Sarath Kodagoda Australia
Guido Bugmann United Kingdom
Gui‐Bin Bian China
Nicola Bellotto United Kingdom
Ling‐Jyh Chen Taiwan
Xin Zhao China
Andrew Liu United States
Wanzeng Kong China
Erwin R. Boer United States
Katharina Eggensperger Germany
Anita Graser relative to Sarath Kodagoda Australia Sarath Kodagoda's profile →
Citations per field
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Sarath Kodagoda · 1×
Citations per year

Countries citing papers authored by Anita Graser

Since Specialization
Citations

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

Fields of papers citing papers by Anita Graser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anita Graser

This figure shows the co-authorship network connecting the top 25 collaborators of Anita Graser. A scholar is included among the top collaborators of Anita Graser based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Anita Graser. Anita Graser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 0
3 1
4 0
5 14
6 6
7 2
8 6
9
Identifying Congestion Patterns in Urban Road Networks Using Floating Car Data
1
10 28
11 10
12 43
13
Learning QGIS 2.0 : use QGIS to create great maps and perform all the geoprocessing tasks you need
0
14
FCD in the Real World– System Capabilities and Applications
5
15 2
16 47
17
Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfacesbreakdown →
564
18 2
19 0
20 25

About Anita Graser

Anita Graser is a scholar working on Transportation, Geography, Planning and Development and Signal Processing, having authored 72 papers that have together received 1.4k indexed citations. Recurring topics across this work include Data Management and Algorithms (16 papers), Human Mobility and Location-Based Analysis (14 papers) and Geographic Information Systems Studies (11 papers). The work is most often cited by research in Human-Computer Interaction (187 citations), Cognitive Neuroscience (623 citations) and Transportation (170 citations). Anita Graser has collaborated with scholars based in Germany, Austria and United Kingdom. Frequent co-authors include Hubert Cecotti, Ivan Volosyak, Oleg Ivlev, Johannes Asamer, Mario Ruthmair, Markus Straub, Oliver Lang, Peter Widhalm, Norbert Brändle and Kenneth J. Hunt. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and Transportation Research Part D Transport and Environment.

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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