Marko Arsenović

3.2k total citations · 2 hit papers
16 papers, 1.9k citations indexed

About

Marko Arsenović is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Marko Arsenović has authored 16 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Computer Networks and Communications and 3 papers in Information Systems. Recurrent topics in Marko Arsenović's work include Network Security and Intrusion Detection (3 papers), Plant Disease Management Techniques (2 papers) and Internet Traffic Analysis and Secure E-voting (2 papers). Marko Arsenović is often cited by papers focused on Network Security and Intrusion Detection (3 papers), Plant Disease Management Techniques (2 papers) and Internet Traffic Analysis and Secure E-voting (2 papers). Marko Arsenović collaborates with scholars based in Serbia and Italy. Marko Arsenović's co-authors include Srdjan Sladojević, Andraš Anderla, Darko Stefanović, Dubravko Ćulibrk, Bojаn Lаlić, L. Cvetićanin and Sonja Ristić and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Sciences and Symmetry.

In The Last Decade

Marko Arsenović

13 papers receiving 1.7k citations

Hit Papers

Deep Neural Networks Based Recognition of Plant Diseases ... 2016 2026 2019 2022 2016 2019 250 500 750 1000

Peers

Marko Arsenović
Marko Arsenović
Citations per year, relative to Marko Arsenović Marko Arsenović (= 1×) peers Andraš Anderla

Countries citing papers authored by Marko Arsenović

Since Specialization
Citations

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

Fields of papers citing papers by Marko Arsenović

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marko Arsenović

This figure shows the co-authorship network connecting the top 25 collaborators of Marko Arsenović. A scholar is included among the top collaborators of Marko Arsenović 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 Marko Arsenović. Marko Arsenović is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Cvetićanin, L. & Marko Arsenović. (2025). Prediction Models for Diabetes in Children and Adolescents: A Review. Applied Sciences. 15(6). 2906–2906.
2.
Sladojević, Srdjan, et al.. (2025). Analysis of different IDS-based machine learning models for secure data transmission in IoT networks. Open Computer Science. 15(1).
3.
Sladojević, Srdjan, et al.. (2024). Mobile ECG Devices Selection. SHILAP Revista de lepidopterología. 18(2). 319–330.
4.
Sladojević, Srdjan, et al.. (2024). Advancements in Mobile-Based Air Pollution Detection: From Literature Review to Practical Implementation. Journal of Sensors. 2024. 1–17. 1 indexed citations
6.
Anderla, Andraš, et al.. (2024). Additive Manufacturing Processes: A Systematic Literature Review. 1–6. 1 indexed citations
7.
Sladojević, Srdjan, et al.. (2022). Machine learning driven course recommendation system. 1–5. 2 indexed citations
8.
Arsenović, Marko, et al.. (2022). Cryptocurrency Price Prediction Using Deep Learning. 233–238. 4 indexed citations
9.
Sladojević, Srdjan, et al.. (2019). Credit Card Fraud Detection - Machine Learning methods. 1–5. 174 indexed citations
10.
Arsenović, Marko, et al.. (2019). Solving Current Limitations of Deep Learning Based Approaches for Plant Disease Detection. Symmetry. 11(7). 939–939. 332 indexed citations breakdown →
11.
Sladojević, Srdjan, et al.. (2018). Telecommunication Services Churn Prediction - Deep Learning Approach. 420–425. 12 indexed citations
12.
Sladojević, Srdjan, et al.. (2018). Convolutional Neural Network Based SMS Spam Detection. 1–4. 28 indexed citations
13.
Arsenović, Marko, Srdjan Sladojević, Darko Stefanović, & Andraš Anderla. (2018). Deep neural network ensemble architecture for eye movements classification. 1–4. 13 indexed citations
14.
Arsenović, Marko, Srdjan Sladojević, Andraš Anderla, Darko Stefanović, & Bojаn Lаlić. (2017). Deep learning powered automated tool for generating image based datasets. 115 3. 13–17. 3 indexed citations
15.
Arsenović, Marko, Srdjan Sladojević, Andraš Anderla, & Darko Stefanović. (2017). FaceTime — Deep learning based face recognition attendance system. 53–58. 107 indexed citations
16.
Sladojević, Srdjan, Marko Arsenović, Andraš Anderla, Dubravko Ćulibrk, & Darko Stefanović. (2016). Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification. Computational Intelligence and Neuroscience. 2016. 1–11. 1199 indexed citations breakdown →

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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