Milan Tuba

6.3k total citations
160 papers, 3.7k citations indexed

About

Milan Tuba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Milan Tuba has authored 160 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Artificial Intelligence, 41 papers in Computer Vision and Pattern Recognition and 32 papers in Computer Networks and Communications. Recurrent topics in Milan Tuba's work include Metaheuristic Optimization Algorithms Research (56 papers), Advanced Multi-Objective Optimization Algorithms (22 papers) and Evolutionary Algorithms and Applications (19 papers). Milan Tuba is often cited by papers focused on Metaheuristic Optimization Algorithms Research (56 papers), Advanced Multi-Objective Optimization Algorithms (22 papers) and Evolutionary Algorithms and Applications (19 papers). Milan Tuba collaborates with scholars based in Serbia, Portugal and Romania. Milan Tuba's co-authors include Nebojša Bačanin, Eva Tuba, Raka Jovanović, Ivana Strumberger, Adis Alihodžić, Marko Beko, Timea Bezdan, Ivona Brajević, Miodrag Živković and Dana Simian and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLANT PHYSIOLOGY and European Journal of Operational Research.

In The Last Decade

Milan Tuba

154 papers receiving 3.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Milan Tuba Serbia 36 1.8k 874 850 677 502 160 3.7k
Mohamed Abouhawwash Egypt 29 1.6k 0.8× 652 0.7× 571 0.7× 808 1.2× 587 1.2× 210 3.9k
Celal Öztürk Türkiye 26 2.3k 1.3× 1.4k 1.6× 631 0.7× 854 1.3× 569 1.1× 67 4.8k
Yue‐Jiao Gong China 33 2.2k 1.2× 870 1.0× 631 0.7× 586 0.9× 1.3k 2.5× 140 4.5k
Jiujun Cheng China 32 1.9k 1.0× 776 0.9× 469 0.6× 940 1.4× 594 1.2× 95 3.8k
Xingjuan Cai China 32 2.0k 1.1× 1.4k 1.7× 682 0.8× 630 0.9× 749 1.5× 130 4.8k
Pavel Trojovský Czechia 29 1.9k 1.1× 431 0.5× 576 0.7× 992 1.5× 676 1.3× 119 4.4k
Reda Mohamed Egypt 29 1.7k 0.9× 488 0.6× 563 0.7× 697 1.0× 559 1.1× 82 3.4k
Kuangrong Hao China 29 1.2k 0.7× 753 0.9× 578 0.7× 459 0.7× 482 1.0× 262 3.3k
Ying Gao China 32 1.1k 0.6× 775 0.9× 462 0.5× 454 0.7× 893 1.8× 205 3.9k
Yongquan Zhou China 41 3.4k 1.8× 577 0.7× 1.0k 1.2× 821 1.2× 1.3k 2.5× 302 6.2k

Countries citing papers authored by Milan Tuba

Since Specialization
Citations

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

Fields of papers citing papers by Milan Tuba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milan Tuba

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Tuba. A scholar is included among the top collaborators of Milan Tuba 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 Milan Tuba. Milan Tuba 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
1.
Tuba, Milan, et al.. (2023). ICT Systems and Sustainability. Lecture notes in networks and systems. 2 indexed citations
2.
Tuba, Eva, et al.. (2022). Acute Lymphoblastic Leukemia Detection by Tuned Convolutional Neural Network. 1–4. 7 indexed citations
3.
Bačanin, Nebojša, Timea Bezdan, Eva Tuba, Ivana Strumberger, & Milan Tuba. (2020). Monarch Butterfly Optimization Based Convolutional Neural Network Design. Mathematics. 8(6). 936–936. 49 indexed citations
4.
Bačanin, Nebojša, Timea Bezdan, Eva Tuba, Ivana Strumberger, & Milan Tuba. (2020). Optimizing Convolutional Neural Network Hyperparameters by Enhanced Swarm Intelligence Metaheuristics. Algorithms. 13(3). 67–67. 102 indexed citations
5.
Strumberger, Ivana, Nebojša Bačanin, Milan Tuba, & Eva Tuba. (2019). Resource Scheduling in Cloud Computing Based on a Hybridized Whale Optimization Algorithm. Applied Sciences. 9(22). 4893–4893. 82 indexed citations
6.
Strumberger, Ivana, Milan Tuba, Nebojša Bačanin, & Eva Tuba. (2019). Cloudlet Scheduling by Hybridized Monarch Butterfly Optimization Algorithm. Journal of Sensor and Actuator Networks. 8(3). 44–44. 30 indexed citations
7.
Strumberger, Ivana, Miroslav Minović, Milan Tuba, & Nebojša Bačanin. (2019). Performance of Elephant Herding Optimization and Tree Growth Algorithm Adapted for Node Localization in Wireless Sensor Networks. Sensors. 19(11). 2515–2515. 94 indexed citations
8.
Tuba, Eva, Raka Jovanović, & Milan Tuba. (2017). Plant Diseases Detection Based on Color Features and Kapur’S Method. WSEAS Transactions on Information Science and Applications archive. 14. 2 indexed citations
9.
Bačanin, Nebojša & Milan Tuba. (2014). Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint. The Scientific World JOURNAL. 2014. 1–16. 82 indexed citations
10.
Tuba, Milan. (2014). Multilevel image thresholding by nature-inspired algorithms: A short review. SHILAP Revista de lepidopterología. 41 indexed citations
11.
Tuba, Milan, et al.. (2012). An object-oriented implementation of the firefly algorithm for continuous unconstrained optimization problems. 411–416. 1 indexed citations
12.
Tuba, Milan. (2010). An algorithm for the network design problem based on the maximum entropy method. 206–211. 2 indexed citations
13.
Tuba, Milan, et al.. (2010). Relation between successfulness of birthday attack on digital signature and hash function irregularity. WSEAS Transactions on Information Science and Applications archive. 7(2). 186–195.
14.
Jovanović, Raka, Milan Tuba, & Dana Simian. (2009). Analysis of parallel implementations of the ant colony optimization applied to the minimum weight vertex cover problem. 13(1). 254–259. 4 indexed citations
15.
Tuba, Milan, et al.. (2009). Design of an intrusion detection system based on Bayesian networks. WSEAS Transactions on Computers archive. 8(5). 799–809. 4 indexed citations
16.
Tuba, Milan. (2009). Relation between static and dynamic optimization in computer network routing. International Conference on Artificial Intelligence. 484–489. 2 indexed citations
17.
Tuba, Milan & Raka Jovanović. (2009). An analysis of different variations of ant colony optimization to the minimum weight vertex cover problem. WSEAS Transactions on Information Science and Applications archive. 6(6). 936–945. 18 indexed citations
18.
Jovanović, Raka, Milan Tuba, & Dana Simian. (2008). An object-oriented framework with corresponding graphical user interface for developing ant colony optimization based algorithms. WSEAS Transactions on Computers archive. 7(12). 1948–1957. 12 indexed citations
19.
Marić, Miroslav, Milan Tuba, & Jozef Kratica. (2008). Parameter adjustment for genetic algorithm for two-level hierarchical covering location problem. WSEAS Transactions on Computers archive. 7(6). 746–755. 3 indexed citations
20.
Jovanović, Raka, Milan Tuba, & Dana Simian. (2008). An algorithm for creation of an optimized adaptive grid for improved explicit finite difference scheme. WSEAS Transactions on Mathematics archive. 7(9). 549–558.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026