Jeonghwan Gwak

3.5k total citations · 2 hit papers
128 papers, 2.3k citations indexed

About

Jeonghwan Gwak is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Jeonghwan Gwak has authored 128 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Computer Vision and Pattern Recognition, 41 papers in Artificial Intelligence and 26 papers in Management Science and Operations Research. Recurrent topics in Jeonghwan Gwak's work include Multi-Criteria Decision Making (21 papers), Video Surveillance and Tracking Methods (17 papers) and Fuzzy and Soft Set Theory (12 papers). Jeonghwan Gwak is often cited by papers focused on Multi-Criteria Decision Making (21 papers), Video Surveillance and Tracking Methods (17 papers) and Fuzzy and Soft Set Theory (12 papers). Jeonghwan Gwak collaborates with scholars based in South Korea, Pakistan and India. Jeonghwan Gwak's co-authors include Jaeyong Kang, Zahid Ullah, Thi Kieu Khanh Ho, Moongu Jeon, Muhammad Usman, Naeem Jan, Harish Garg, Soo‐Jin Park, Seongmin Park and Kwang Mong Sim and has published in prestigious journals such as PLoS ONE, Advanced Functional Materials and Scientific Reports.

In The Last Decade

Jeonghwan Gwak

124 papers receiving 2.2k 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.

MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

2021 378 citations Jaeyong Kang, Zahid Ullah et al. profile →
Highly Oxidation‐Resistant and Self‐Healable MXene‐Based Hydrogels for Wearable Strain Sensor

2023 179 citations Jeonghwan Gwak et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jeonghwan Gwak South Korea	24	683	664	542	523	330	128	2.3k
Muazzam Maqsood Pakistan	29	456 0.7×	913 1.4×	546 1.0×	330 0.6×	211 0.6×	84	2.6k
Musaed Alhussein Saudi Arabia	31	587 0.9×	749 1.1×	259 0.5×	405 0.8×	214 0.6×	146	3.2k
M. F. Mridha Bangladesh	27	413 0.6×	1.1k 1.6×	135 0.2×	236 0.5×	163 0.5×	243	2.7k
Adi Alhudhaif Saudi Arabia	27	513 0.8×	630 0.9×	152 0.3×	242 0.5×	137 0.4×	106	2.0k
Muhammad Usman Ghani Khan Pakistan	23	592 0.9×	781 1.2×	281 0.5×	256 0.5×	93 0.3×	112	2.0k
Malika Bendechache Ireland	23	739 1.1×	551 0.8×	521 1.0×	411 0.8×	158 0.5×	79	1.8k
Mohamed Hammad Egypt	28	494 0.7×	822 1.2×	178 0.3×	463 0.9×	525 1.6×	78	2.8k
Gustavo Ramírez-González Colombia	23	533 0.8×	594 0.9×	154 0.3×	349 0.7×	178 0.5×	94	2.5k
Habibollah Haron Malaysia	29	630 0.9×	907 1.4×	114 0.2×	292 0.6×	404 1.2×	144	3.1k
M. Pallikonda Rajasekaran India	25	592 0.9×	329 0.5×	417 0.8×	176 0.3×	262 0.8×	176	2.0k

Countries citing papers authored by Jeonghwan Gwak

Since Specialization

Citations

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

Fields of papers citing papers by Jeonghwan Gwak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeonghwan Gwak

This figure shows the co-authorship network connecting the top 25 collaborators of Jeonghwan Gwak. A scholar is included among the top collaborators of Jeonghwan Gwak 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 Jeonghwan Gwak. Jeonghwan Gwak 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

Khan, Asifullah, Zunaira Rauf, Abdul Rehman Khan, et al.. (2025). A Recent Survey of Vision Transformers for Medical Image Segmentation. IEEE Access. 13. 191824–191849. 1 indexed citations

Ullah, Zahid, et al.. (2024). Multi-teacher cross-modal distillation with cooperative deep supervision fusion learning for unimodal segmentation. Knowledge-Based Systems. 297. 111854–111854. 9 indexed citations

Jan, Naeem, Jeonghwan Gwak, Dragan Pamucar, & Luis Martı́nez. (2023). Hybrid integrated decision-making model for operating system based on complex intuitionistic fuzzy and soft information. Information Sciences. 651. 119592–119592. 8 indexed citations

Garg, Harish, Zeeshan Ali, Jeonghwan Gwak, & Ibrahim M. Hezam. (2023). Generalized Heronian Mean Operators Based on Archimedean T‐Norms of the Complex Picture Fuzzy Information and Their Application to Decision‐Making. Mathematical Problems in Engineering. 2023(1). 5 indexed citations

Gwak, Jeonghwan, et al.. (2023). A new approach to investigate the effects of artificial neural networks based on bipolar complex spherical fuzzy information. Complex & Intelligent Systems. 9(4). 4591–4614. 13 indexed citations

Farooq, Muhammad Umar, Zahid Ullah, & Jeonghwan Gwak. (2023). Residual attention based uncertainty-guided mean teacher model for semi-supervised breast masses segmentation in 2D ultrasonography. Computerized Medical Imaging and Graphics. 104. 102173–102173. 19 indexed citations

Jan, Naeem, Jeonghwan Gwak, & Dragan Pamucar. (2023). A robust hybrid decision making model for Human-Computer interaction in the environment of Bipolar complex picture fuzzy soft Sets. Information Sciences. 645. 119163–119163. 16 indexed citations

Kim, Minhee, et al.. (2023). A comprehensive research setup for monitoring Alzheimer’s disease using EEG, fNIRS, and Gait analysis. Biomedical Engineering Letters. 14(1). 13–21. 6 indexed citations

Din, Fakhrud, et al.. (2022). Fuzzy Adaptive Teaching Learning-Based Optimization for Solving Unconstrained Numerical Optimization Problems. Mathematical Problems in Engineering. 2022. 1–17. 3 indexed citations

10.

Jan, Naeem, Jeonghwan Gwak, Jiaming Pei, Rabia Maqsood, & Abdul Nasir. (2022). Analysis of Networks and Digital Systems by Using the Novel Technique Based on Complex Fuzzy Soft Information. IEEE Transactions on Consumer Electronics. 69(2). 183–193. 23 indexed citations

11.

Jan, Naeem, et al.. (2022). Investigation of Blockchain Technology by Using the Innovative Concepts of Complex Pythagorean Fuzzy Soft Information. Complexity. 2022(1). 4 indexed citations

12.

Fayaz, Muhammad, et al.. (2021). An Effective Classification Methodology for Brain MRI Classification Based on Statistical Features, DWT and Blended ANN. IEEE Access. 9. 159146–159159. 5 indexed citations

13.

Kang, Jaeyong & Jeonghwan Gwak. (2021). Deep Learning-Based Brain Tumor Classification in MRI images using Ensemble of Deep Features. Journal of the Korea Society of Computer and Information. 26(7). 37–44. 3 indexed citations

14.

Khan, Junaid, et al.. (2021). An Improved Alpha Beta Filter Using a Deep Extreme Learning Machine. IEEE Access. 9. 61548–61564. 20 indexed citations

15.

Khan, Inam Ullah, Muhammad Abul Hassan, Muhammad Fayaz, Jeonghwan Gwak, & Muhammad Adnan Aziz. (2021). Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS. Computers, materials & continua/Computers, materials & continua (Print). 70(2). 3653–3666. 14 indexed citations

16.

Mehmood, Gulzar, Muhammad Zahid Khan, Muhammad Fayaz, et al.. (2021). An Energy-Efficient Mobile Agent-Based Data Aggregation Scheme for Wireless Body Area Networks. Computers, materials & continua/Computers, materials & continua (Print). 70(3). 5929–5948. 17 indexed citations

17.

Kang, Jaeyong & Jeonghwan Gwak. (2020). KD-ResUNet++: Automatic Polyp Segmentation via Self-Knowledge Distillation.. MediaEval. 2 indexed citations

18.

Gwak, Jeonghwan & Kwang Mong Sim. (2011). Bayesian Learning based Negotiation Agents for Supporting Negotiation with Incomplete Information. Lecture notes in computer science. 2188(1). 163–168. 13 indexed citations

19.

Gwak, Jeonghwan, Kwang Mong Sim, & Minjie Zhang. (2010). Finding near-optimal strategies for negotiation with incomplete information using a diversity controlling EDA. 1–7. 3 indexed citations

20.

Gwak, Jeonghwan & Kwang Mong Sim. (2010). Co-evolving Best Response Strategies for P-S-Optimizing Negotiation using Evolutionary Algorithms. Lecture notes in computer science. 2180(1). 13–18. 2 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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