Ivan Marković
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- Advanced Vision and Imaging 11
- Robotic Path Planning Algorithms 10
- Video Surveillance and Tracking Methods 7
- Aerospace Engineering top 5%
- Robotics and Sensor-Based Localization 26
- Instrumentation top 10%
- Geology top 5%
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- Target Tracking and Data Fusion in Sensor Networks 19
- Bayesian Methods and Mixture Models 6
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- Indoor and Outdoor Localization Technologies 7
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- Speech and Audio Processing 6
Ivan Marković
55 papers receiving 775 citations
Peers
Comparison fields: 5 of 76
- Computer Vision and Pattern Recognition 334
- Aerospace Engineering 395
- Instrumentation 52
- Geology 75
- Industrial and Manufacturing Engineering 69
Countries citing papers authored by Ivan Marković
This map shows the geographic impact of Ivan Marković'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 Ivan Marković with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Marković more than expected).
Fields of papers citing papers by Ivan Marković
This network shows the impact of papers produced by Ivan Marković. 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 Ivan Marković. The network helps show where Ivan Marković may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Ivan Marković, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 10 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 0 | |
| 8 | 2020 | 9 | |
| 9 | 2020 | 15 | |
| 10 | 2019 | 3 | |
| 11 | 2018 | 44 | |
| 12 | 2017 | 15 | |
| 13 | Multitarget tracking with the von Mises-Fisher filter and probabilistic data association | 2016 | 5 |
| 14 | 2016 | 7 | |
| 15 | 2015 | 15 | |
| 16 | Direction-only tracking of moving objects on the unit sphere via probabilistic data association | 2014 | 6 |
| 17 | Tracking of multiple moving objects on the unit sphere using a multiple-camera system on a mobile robot | 2014 | 1 |
| 18 | People Tracking with Heterogeneous Sensors using JPDAF with Entropy Based Track Management | 2011 | 9 |
| 19 | 2010 | 45 | |
| 20 | 1988 | 9 |
About Ivan Marković
Ivan Marković is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Instrumentation, Artificial Intelligence and Signal Processing, having authored 61 papers that have together received 802 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (26 papers), Target Tracking and Data Fusion in Sensor Networks (19 papers), Advanced Vision and Imaging (11 papers), Robotic Path Planning Algorithms (10 papers), Indoor and Outdoor Localization Technologies (7 papers), Video Surveillance and Tracking Methods (7 papers), Bayesian Methods and Mixture Models (6 papers) and Speech and Audio Processing (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (334 citations), Aerospace Engineering (395 citations), Instrumentation (52 citations), Geology (75 citations) and Industrial and Manufacturing Engineering (69 citations). Ivan Marković has collaborated with scholars based in Croatia, Czechia and Serbia. Frequent co-authors include Ivan Petrović, Josip Ćesić, Igor Cvišić, Tomislav Petković, Björn Hein, Marija Seder, Dana Kulić, Libor Přeučil, Vladimir Marić and Wolfgang Merkt. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Signal Processing Letters, IEEE Transactions on Robotics, Advanced Robotics and Applied Soft Computing.
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.