Eva Tuba
Impact in
- Artificial Intelligence top 2%
- Metaheuristic Optimization Algorithms Research
- Machine Learning and ELM
- Evolutionary Algorithms and Applications
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- Advanced Neural Network Applications
- Robotic Path Planning Algorithms
Papers in
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- Metaheuristic Optimization Algorithms Research 23
- Neural Networks and Applications 7
- Machine Learning and ELM 5
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- Advanced Neural Network Applications 7
- Robotic Path Planning Algorithms 6
- Face and Expression Recognition 5
- Co-authors
- Milan Tuba (60 shared papers)Nebojša Bačanin (31 shared papers)Ivana Strumberger (28 shared papers)Timea Bezdan (8 shared papers)Miodrag Živković (6 shared papers)Edin Dolićanin (7 shared papers)Marko Beko (12 shared papers)Raka Jovanović (11 shared papers)
In The Last Decade
Eva Tuba
73 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 796
- Computer Vision and Pattern Recognition 500
- Computer Networks and Communications 419
- Information Systems 276
- Media Technology 104
Countries citing papers authored by Eva Tuba
This map shows the geographic impact of Eva Tuba'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 Eva Tuba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Tuba more than expected).
Fields of papers citing papers by Eva Tuba
This network shows the impact of papers produced by Eva Tuba. 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 Eva Tuba. The network helps show where Eva Tuba may publish in the future.
Co-authors
The 24 scholars most cited alongside Eva Tuba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 102 | |
| 2 | 2019 | 82 | |
| 3 | 2019 | 78 | |
| 4 | 2020 | 68 | |
| 5 | 2020 | 66 | |
| 6 | 2021 | 65 | |
| 7 | 2019 | 65 | |
| 8 | 2019 | 59 | |
| 9 | 2017 | 54 | |
| 10 | 2020 | 49 | |
| 11 | 2016 | 48 | |
| 12 | 2018 | 48 | |
| 13 | 2019 | 47 | |
| 14 | 2017 | 44 | |
| 15 | 2017 | 40 | |
| 16 | 2020 | 38 | |
| 17 | 2017 | 36 | |
| 18 | 2017 | 35 | |
| 19 | 2018 | 35 | |
| 20 | 2017 | 34 |
About Eva Tuba
Eva Tuba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Electrical and Electronic Engineering and Media Technology, having authored 76 papers that have together received 1.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (23 papers), Energy Efficient Wireless Sensor Networks (8 papers), Advanced Neural Network Applications (7 papers), Neural Networks and Applications (7 papers), Robotic Path Planning Algorithms (6 papers), Smart Agriculture and AI (6 papers), Face and Expression Recognition (5 papers) and Machine Learning and ELM (5 papers). The work is most often cited by research in Artificial Intelligence (796 citations), Computer Vision and Pattern Recognition (500 citations), Computer Networks and Communications (419 citations), Information Systems (276 citations) and Media Technology (104 citations). Eva Tuba has collaborated with scholars based in Serbia, Portugal and Qatar. Frequent co-authors include Milan Tuba, Nebojša Bačanin, Ivana Strumberger, Timea Bezdan, Miodrag Živković, Edin Dolićanin, Marko Beko, Raka Jovanović, Adis Alihodžić and Dana Simian. Their work appears in journals such as Studies in Informatics and Control, Applied Sciences, Journal of Intelligent & Fuzzy Systems, Journal of King Saud University - Computer and Information Sciences and Journal of Sensor and Actuator Networks.
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.