Marko Šarac

34 papers receiving 371 citations

Peers

Marko Šarac
Comparison fields: 5 of 87
  • Signal Processing 79
  • Information Systems 113
  • Artificial Intelligence 129
  • Computer Vision and Pattern Recognition 82
  • Computer Networks and Communications 80
Replace Marco Luca Sbodio with:
Marco Luca Sbodio Ireland
Michael Goebel United States
Mohammed Elbes Jordan
Wasif Nisar Pakistan
Ruslan Dautov United States
Niranjan N. Chiplunkar India
Gourav Bathla India
Valerie Guralnik United States
P. Radha Krishna India
Agnès Voisard Germany
Marko Šarac relative to Marco Luca Sbodio Ireland Marco Luca Sbodio's profile →
Citations per field
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Citations per year

Countries citing papers authored by Marko Šarac

Since Specialization
Citations

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

Fields of papers citing papers by Marko Šarac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marko Šarac, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marko Šarac Line = papers co-authored together Marko Šarac links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202047
2 202143
3 202241
4 202239
5 201929
6
Moth Search Algorithm for Drone Placement Problem
201824
7 201624
8 202416
9 202416
10
IT audit in accordance with Cobit standard
201015
11
Hybridized Monarch Butterfly Algorithm for Global Optimization Problems
201811
12 202110
13 201910
14 20109
15
The importance of the using software tools for learning modern cryptography
20188
16 20218
17 20235
18 20225
19
Information technology governance — COBIT model
20114
20 20174

About Marko Šarac

Marko Šarac is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Information Systems, having authored 37 papers that have together received 397 indexed citations. Recurring topics across this work include Biometric Identification and Security (4 papers), IoT and Edge/Fog Computing (4 papers), Big Data and Business Intelligence (4 papers), Authorship Attribution and Profiling (3 papers), Advanced Malware Detection Techniques (3 papers), Chaos-based Image/Signal Encryption (3 papers), Advanced Steganography and Watermarking Techniques (2 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Signal Processing (79 citations), Information Systems (113 citations), Artificial Intelligence (129 citations), Computer Vision and Pattern Recognition (82 citations) and Computer Networks and Communications (80 citations). Marko Šarac has collaborated with scholars based in Serbia, India and Taiwan. Frequent co-authors include Nebojša Bačanin, Saša Adamović, Miodrag Živković, Ivana Strumberger, Muzafer Saračević, Nemanja Maček, Milan Milosavljević, Dušan Marković, Fadi Al‐Turjman and Cătălin Stoean. Their work appears in journals such as Multimedia Tools and Applications, International journal of engineering education, Future Generation Computer Systems, Sustainable Computing Informatics and Systems and Engineering Applications of Artificial Intelligence.

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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