Miloš Krstajić
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Statistical and Nonlinear Physics top 10%
- Sociology and Political Science
- Co-authors
- Daniel A. KeimEnrico BertiniJing YangWilliam RibarskyFlorian MansmannGennady AndrienkoSlava KisilevichNatalia Andrienko
- Topics
- Data Visualization and Analytics (14 papers)Advanced Text Analysis Techniques (6 papers)Video Analysis and Summarization (6 papers)
- Partner nations
- GermanyUnited StatesItaly
In The Last Decade
Miloš Krstajić
15 papers receiving 388 citations
Peers
Comparison fields: 5 of 61
- Computer Vision and Pattern Recognition 292
- Artificial Intelligence 124
- Signal Processing 94
- Statistical and Nonlinear Physics 86
- Sociology and Political Science 71
Countries citing papers authored by Miloš Krstajić
This map shows the geographic impact of Miloš Krstajić'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 Miloš Krstajić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miloš Krstajić more than expected).
Fields of papers citing papers by Miloš Krstajić
This network shows the impact of papers produced by Miloš Krstajić. 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 Miloš Krstajić. The network helps show where Miloš Krstajić may publish in the future.
Co-authorship network of co-authors of Miloš Krstajić
This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Krstajić. A scholar is included among the top collaborators of Miloš Krstajić 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 Miloš Krstajić. Miloš Krstajić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 7 | |
| 3 | 15 | |
| 4 | Solving Problems with Visual Analytics : Challenges and Applications | 14 |
| 5 | 7 | |
| 6 | Getting there first : real-time detection of real-world incidents on Twitter | 21 |
| 7 | 117 | |
| 8 | 9 | |
| 9 | Real-Time Visualization of Streaming Text Data: Tasks and Challenges | 11 |
| 10 | 6 | |
| 11 | 89 | |
| 12 | 19 | |
| 13 | 10 | |
| 14 | 2 | |
| 15 | 70 | |
| 16 | Large-scale Comparative Sentiment Analysis of News Articles | 4 |
About Miloš Krstajić
Miloš Krstajić is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Statistical and Nonlinear Physics, having authored 16 papers that have together received 419 indexed citations. Recurring topics across this work include Data Visualization and Analytics (14 papers), Advanced Text Analysis Techniques (6 papers) and Video Analysis and Summarization (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (292 citations), Signal Processing (94 citations) and Statistical and Nonlinear Physics (86 citations). Miloš Krstajić has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Daniel A. Keim, Enrico Bertini, Jing Yang, William Ribarsky, Florian Mansmann, Gennady Andrienko, Slava Kisilevich, Natalia Andrienko, Christian Rohrdantz and Andreas Weiler. Their work appears in journals such as Computer, IEEE Transactions on Visualization and Computer Graphics 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.