Eduard Babulak

32 papers receiving 173 citations

Peers

Eduard Babulak
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 52
  • Computer Networks and Communications 38
  • Industrial and Manufacturing Engineering 25
  • Information Systems 21
  • Artificial Intelligence 21
Replace Mohamed Mhiri with:
Mohamed Mhiri Tunisia
D Rajeswari India
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V. Asha India
Safeeullah Soomro Bahrain
Miguel Botto-Tobar Ecuador
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Shaheen Khatoon Saudi Arabia
Olutosin Taiwo South Africa
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Citations per field
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Citations per year

Countries citing papers authored by Eduard Babulak

Since Specialization
Citations

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

Fields of papers citing papers by Eduard Babulak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduard Babulak

This figure shows the co-authorship network connecting the top 25 collaborators of Eduard Babulak. A scholar is included among the top collaborators of Eduard Babulak 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 Eduard Babulak. Eduard Babulak 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 3
2
Implementing canny edge detection algorithm for noisy image
0
3
SL-RPL: Stability-Aware Load Balancing for RPL
4
4
COVID-19 & Cyber Security Challenges US, Canada & Korea
0
5
SL-RPL: Stability-Aware Load Balancing for RPL.
2
6
Third Millennium Smart Cyberspace
1
7 5
8 0
9
Intellectual Capital Optimisation in Microeconomic Sphere
2
10 1
11 1
12 7
13
Information Cyberspace and Future Cyber Homes
5
14 5
15
Automated environment via information cyberspace.
2
16 25
17 1
18
The university network model for the quality of service provision analysis
6
19
INTERDISCIPLINARITY AND UBIQUITOUS INTERNET TECHNOLOGIES IN SUPPORT OF AUTOMATION
5
20 5

About Eduard Babulak

Eduard Babulak is a scholar working on Computer Networks and Communications, Industrial and Manufacturing Engineering and Management Information Systems, having authored 43 papers that have together received 190 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (7 papers), Context-Aware Activity Recognition Systems (7 papers) and Indoor and Outdoor Localization Technologies (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (52 citations), Industrial and Manufacturing Engineering (25 citations) and Media Technology (21 citations). Eduard Babulak has collaborated with scholars based in United States, United Kingdom and Fiji. Frequent co-authors include Ming Wang, Rolando Carrasco, Feng Wang, Yongning Tang, Reza Ebrahimi Atani, Benjamin Fabian, Sandeep Kumar Arora, Mohammed A. AlZain, S. N. Kumar and Lavish Kansal. Their work appears in journals such as International Journal of Medical Informatics, Security and Communication Networks and Journal of Communications and Information 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.

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