Eva Tuba

3.4k total citations
76 papers, 1.7k citations indexed

About

Eva Tuba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Eva Tuba has authored 76 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 34 papers in Computer Vision and Pattern Recognition and 15 papers in Computer Networks and Communications. Recurrent topics in Eva Tuba's work include Metaheuristic Optimization Algorithms Research (23 papers), Energy Efficient Wireless Sensor Networks (8 papers) and Advanced Neural Network Applications (7 papers). Eva Tuba is often cited by papers focused on Metaheuristic Optimization Algorithms Research (23 papers), Energy Efficient Wireless Sensor Networks (8 papers) and Advanced Neural Network Applications (7 papers). Eva Tuba collaborates with scholars based in Serbia, Portugal and Qatar. Eva Tuba's co-authors include Milan Tuba, Nebojša Bačanin, Ivana Strumberger, Timea Bezdan, Miodrag Živković, Edin Dolićanin, Marko Beko, Raka Jovanović, Adis Alihodžić and Dana Simian and has published in prestigious journals such as Applied Sciences, Journal of King Saud University - Computer and Information Sciences and Journal of Intelligent & Fuzzy Systems.

In The Last Decade

Eva Tuba

73 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eva Tuba Serbia	26	796	500	419	276	224	76	1.7k
Ivana Strumberger Serbia	27	1.0k 1.3×	344 0.7×	501 1.2×	388 1.4×	382 1.7×	71	2.0k
Zhaoquan Gu China	23	766 1.0×	547 1.1×	578 1.4×	300 1.1×	358 1.6×	165	2.2k
K. Venkatachalam Czechia	23	713 0.9×	343 0.7×	304 0.7×	254 0.9×	278 1.2×	93	1.8k
Xiao Chen China	20	443 0.6×	458 0.9×	485 1.2×	367 1.3×	319 1.4×	130	2.1k
Daniel Yeung China	21	1.0k 1.3×	700 1.4×	311 0.7×	214 0.8×	266 1.2×	135	2.0k
Weiguo Sheng China	29	1.0k 1.3×	486 1.0×	713 1.7×	159 0.6×	199 0.9×	105	2.5k
Liqiang Wang United States	23	750 0.9×	430 0.9×	780 1.9×	410 1.5×	121 0.5×	125	1.9k
Tao Ye China	23	497 0.6×	421 0.8×	571 1.4×	161 0.6×	149 0.7×	109	1.5k
Kaiyong Zhao Hong Kong	15	864 1.1×	421 0.8×	270 0.6×	147 0.5×	181 0.8×	30	1.8k
Gulshan Kumar India	18	846 1.1×	295 0.6×	727 1.7×	204 0.7×	224 1.0×	45	1.9k

Countries citing papers authored by Eva Tuba

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Eva Tuba

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

All Works

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20 of 20 papers shown

Jovanović, Luka, Miodrag Živković, Miloš Antonijević, et al.. (2024). Audio analysis with convolutional neural networks and boosting algorithms tuned by metaheuristics for respiratory condition classification. Journal of King Saud University - Computer and Information Sciences. 36(10). 102261–102261. 10 indexed citations

Tuba, Eva, et al.. (2022). Acute Lymphoblastic Leukemia Detection by Tuned Convolutional Neural Network. 1–4. 7 indexed citations

Bezdan, Timea, Miodrag Živković, Nebojša Bačanin, et al.. (2021). Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm. Journal of Intelligent & Fuzzy Systems. 42(1). 411–423. 65 indexed citations

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

Manzoni, Luca, Luca Mariot, & Eva Tuba. (2020). Balanced crossover operators in Genetic Algorithms. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 38 indexed citations

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

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

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

Tuba, Eva, et al.. (2019). Brain Image Segmentation Based on Firefly Algorithm Combined with K-means Clustering. Studies in Informatics and Control. 28(2). 65 indexed citations

10.

Tuba, Eva, Raka Jovanović, Dejan Živković, Marko Beko, & Milan Tuba. (2019). Clustering Algorithm Optimized by Brain Storm Optimization for Digital Image Segmentation. 1–6. 3 indexed citations

11.

Tuba, Eva, Dana Simian, Edin Dolićanin, Raka Jovanović, & Milan Tuba. (2018). Energy Efficient Sink Placement in Wireless Sensor Networks by Brain Storm Optimization Algorithm. 718–723. 13 indexed citations

12.

Tuba, Eva, Edin Dolićanin, & Milan Tuba. (2018). Water Cycle Algorithm for Robot Path Planning. 1–6. 6 indexed citations

13.

Tuba, Eva, et al.. (2018). Chaotic elephant herding optimization algorithm. 213–216. 22 indexed citations

14.

Tuba, Eva, et al.. (2018). Efficient drone placement for wireless sensor networks coverage by bare bones fireworks algorithm. 1–5. 5 indexed citations

15.

Tuba, Eva & Zorica Stanimirović. (2017). Elephant herding optimization algorithm for support vector machine parameters tuning. 1–4. 36 indexed citations

16.

Tuba, Eva, et al.. (2017). Medical Ultrasound Image Speckle Noise Reduction by Adaptive Median Filter. 14. 11 indexed citations

17.

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

18.

Tuba, Eva, Milan Tuba, & Dana Simian. (2017). Support vector machine optimized by firefly algorithm for emphysema classification in lung tissue CT images. Digital Library (University of West Bohemia). 4 indexed citations

19.

Tuba, Eva, Milan Tuba, & Dana Simian. (2016). Handwritten digit recognition by support vector machine optimized by Bat algorithm. Digital Library (University of West Bohemia). 25 indexed citations

20.

Tuba, Eva, et al.. (2015). An Algorithm for Medical Magnetic Resonance Image Non-Local Means Denoising. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

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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