Nebojša Bačanin

11.7k total citations · 4 hit papers
282 papers, 5.7k citations indexed

About

Nebojša Bačanin is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nebojša Bačanin has authored 282 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 147 papers in Artificial Intelligence, 55 papers in Computer Networks and Communications and 53 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nebojša Bačanin's work include Metaheuristic Optimization Algorithms Research (52 papers), Anomaly Detection Techniques and Applications (28 papers) and Energy Load and Power Forecasting (22 papers). Nebojša Bačanin is often cited by papers focused on Metaheuristic Optimization Algorithms Research (52 papers), Anomaly Detection Techniques and Applications (28 papers) and Energy Load and Power Forecasting (22 papers). Nebojša Bačanin collaborates with scholars based in Serbia, India and Taiwan. Nebojša Bačanin's co-authors include Milan Tuba, Miodrag Živković, Ivana Strumberger, Timea Bezdan, K. Venkatachalam, Eva Tuba, Miloš Antonijević, Luka Jovanović, Vladimir Šimić and Aleksandar Petrović and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Nebojša Bačanin

259 papers receiving 5.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN)—A Case Study of the Electric Vehicle Selection Problem

2023 97 citations Libor Švadlenka, Stefan Jovčić et al. IEEE Access profile →
Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework

2025 22 citations Miloš Antonijević, Miodrag Živković et al. Scientific Reports profile →
Two-tier deep and machine learning approach optimized by adaptive multi-population firefly algorithm for software defects prediction

2025 22 citations Miodrag Živković, Tamara Živković et al. profile →
A Halton enhanced solution-based Human Evolutionary Algorithm for complex optimization and advanced feature selection problems

2025 19 citations Nebojša Bačanin et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nebojša Bačanin Serbia	42	2.6k	1.2k	1.0k	899	898	282	5.7k
Bo Yang China	35	2.3k 0.9×	1.1k 1.0×	899 0.9×	677 0.8×	578 0.6×	281	5.2k
Chih‐Fong Tsai Taiwan	43	3.8k 1.5×	922 0.8×	665 0.7×	937 1.0×	850 0.9×	141	7.8k
Wei Wei China	51	2.4k 0.9×	2.1k 1.8×	1.5k 1.5×	1.3k 1.5×	1.7k 1.9×	460	8.3k
Absalom E. Ezugwu South Africa	38	3.0k 1.2×	713 0.6×	861 0.9×	558 0.6×	949 1.1×	167	6.7k
Mohammed A. A. Al‐qaness China	44	3.2k 1.2×	1.2k 1.0×	1.2k 1.2×	389 0.4×	1.2k 1.4×	174	7.1k
Bartosz Krawczyk Poland	34	5.0k 1.9×	636 0.5×	1.1k 1.1×	522 0.6×	785 0.9×	135	7.1k
Marcin Woźniak Poland	48	2.1k 0.8×	817 0.7×	823 0.8×	755 0.8×	2.1k 2.3×	273	7.2k
Jia Wu Australia	46	4.5k 1.7×	780 0.7×	465 0.5×	1.5k 1.6×	1.8k 2.0×	356	7.8k
Milan Tuba Serbia	36	1.8k 0.7×	874 0.8×	677 0.7×	435 0.5×	850 0.9×	160	3.7k
Xingjuan Cai China	32	2.0k 0.8×	1.4k 1.2×	630 0.6×	1.3k 1.4×	682 0.8×	130	4.8k

Countries citing papers authored by Nebojša Bačanin

Since Specialization

Citations

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

Fields of papers citing papers by Nebojša Bačanin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nebojša Bačanin

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Jovčić, Stefan, et al.. (2025). A NEW CRITERIA IMPORTANCE ASSESSMENT (CIMAS) METHOD IN MULTI-CRITERIA GROUP DECISION-MAKING: CRITERIA EVALUATION FOR SUPPLIER SELECTION. Facta Universitatis Series Mechanical Engineering. 23(2). 335–335. 4 indexed citations

Jovanović, Luka, Nebojša Bačanin, Aleksandar Petrović, et al.. (2025). Exploring artificial intelligence potential in solar energy production forecasting: Methodology based on modified PSO optimized attention augmented recurrent networks. Sustainable Computing Informatics and Systems. 47. 101174–101174. 3 indexed citations

Jovanović, Luka, Nebojša Bačanin, Miodrag Živković, et al.. (2025). Towards sustainable societies: Convolutional neural networks optimized by modified crayfish optimization algorithm aided by AdaBoost and XGBoost for waste classification tasks. Applied Soft Computing. 175. 113086–113086. 8 indexed citations

Jovanović, Luka, et al.. (2024). Click Fraud Detection with Recurrent Neural Networks Optimized by Adapted Crayfish Optimization Algorithm. 2(4). 230–239. 1 indexed citations

Dev, Nikhil, Raman Kumar, Atul Babbar, et al.. (2024). Performance evaluation methodology for gas turbine power plants using graph theory and combinatorics. International Journal of Hydrogen Energy. 57. 1286–1301. 6 indexed citations

Jovanović, Luka, et al.. (2024). Neurodegenerative Condition Detection Using Modified Metaheuristic for Attention Based Recurrent Neural Networks and Extreme Gradient Boosting Tuning. IEEE Access. 12. 26719–26734. 9 indexed citations

Ala, Ali, Vladimir Šimić, Dragan Pamučar, & Nebojša Bačanin. (2024). Enhancing patient information performance in internet of things-based smart healthcare system: Hybrid artificial intelligence and optimization approaches. Engineering Applications of Artificial Intelligence. 131. 107889–107889. 34 indexed citations

Venkatachalam, K., Vladimir Šimić, Nebojša Bačanin, & Dragan Pamučar. (2024). Optimized deep learning networks for accurate identification of cancer cells in bone marrow. Neural Networks. 181. 106822–106822. 8 indexed citations

Jovanović, Luka, et al.. (2024). YOLOv8 Utilization in Occupational Health and Safety. 182–187. 3 indexed citations

10.

Jovanović, Luka, et al.. (2024). Optimizing Lightweight Recurrent Networks for Solar Forecasting in TinyML: Modified Metaheuristics and Legal Implications. Energies. 18(1). 105–105. 3 indexed citations

11.

Bačanin, Nebojša, et al.. (2023). Diagnostic ability of deep learning in detection of pancreatic tumour. Scientific Reports. 13(1). 9725–9725. 30 indexed citations

12.

Jovanović, Luka, Miloš Antonijević, Boško Nikolić, et al.. (2023). Improving Phishing Website Detection Using a Hybrid Two-level Framework for Feature Selection and XGBoost Tuning. Journal of Web Engineering. 36 indexed citations

13.

Bačanin, Nebojša, Miodrag Živković, Miloš Antonijević, et al.. (2023). Addressing feature selection and extreme learning machine tuning by diversity-oriented social network search: an application for phishing websites detection. Complex & Intelligent Systems. 9(6). 7269–7304. 22 indexed citations

14.

Dobrojević, Miloš, et al.. (2023). Gold Prices Forecasting Using Recurrent Neural Network with Attention Tuned by Metaheuristics. 345–350. 3 indexed citations

15.

Jovanović, Gordana, Mirjana Perišić, Nebojša Bačanin, et al.. (2023). Potential of Coupling Metaheuristics-Optimized-XGBoost and SHAP in Revealing PAHs Environmental Fate. Toxics. 11(4). 394–394. 20 indexed citations

16.

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

17.

Bačanin, Nebojša, et al.. (2022). Application of Machine Learning to Express Measurement Uncertainty. Applied Sciences. 12(17). 8581–8581. 7 indexed citations

18.

Bačanin, Nebojša, Miloš Antonijević, Timea Bezdan, et al.. (2022). Energy efficient offloading mechanism using particle swarm optimization in 5G enabled edge nodes. Cluster Computing. 26(1). 587–598. 34 indexed citations

19.

Bačanin, Nebojša, Timea Bezdan, K. Venkatachalam, & Fadi Al‐Turjman. (2021). Optimized convolutional neural network by firefly algorithm for magnetic resonance image classification of glioma brain tumor grade. Journal of Real-Time Image Processing. 18(4). 1085–1098. 61 indexed citations

20.

Šarac, Marko, et al.. (2021). Increasing privacy and security by integrating a Blockchain Secure Interface into an IoT Device Security Gateway Architecture. Energy Reports. 7. 8075–8082. 43 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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