Heesung Kwon

2.8k total citations · 1 hit paper
106 papers, 2.0k citations indexed

About

Heesung Kwon is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Heesung Kwon has authored 106 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Media Technology, 56 papers in Computer Vision and Pattern Recognition and 28 papers in Aerospace Engineering. Recurrent topics in Heesung Kwon's work include Remote-Sensing Image Classification (59 papers), Remote Sensing and Land Use (25 papers) and Infrared Target Detection Methodologies (19 papers). Heesung Kwon is often cited by papers focused on Remote-Sensing Image Classification (59 papers), Remote Sensing and Land Use (25 papers) and Infrared Target Detection Methodologies (19 papers). Heesung Kwon collaborates with scholars based in United States, United Kingdom and South Korea. Heesung Kwon's co-authors include Nasser M. Nasrabadi, Prudhvi Gurram, Hyungtae Lee, Sungmin Eum, John G. Rogers, Maggie Wigness, David K. Han, Rama Chellappa, Tao Han and Benjamin M. Marlin and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Heesung Kwon

102 papers receiving 1.9k citations

Hit Papers

Kernel RX-algorithm: a nonlinear anomaly detector for hyp... 2005 2026 2012 2019 2005 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heesung Kwon United States 19 1.4k 723 647 381 352 106 2.0k
Weiying Xie China 32 2.2k 1.6× 775 1.1× 1.1k 1.6× 538 1.4× 395 1.1× 113 2.9k
Xiaorui Ma China 27 962 0.7× 526 0.7× 662 1.0× 329 0.9× 542 1.5× 63 2.2k
Mingyang Zhang China 27 1.1k 0.8× 682 0.9× 515 0.8× 512 1.3× 142 0.4× 118 2.0k
Le Sun China 27 2.1k 1.5× 1.1k 1.5× 978 1.5× 238 0.6× 118 0.3× 117 2.6k
Yang Xu China 19 975 0.7× 398 0.6× 478 0.7× 290 0.8× 129 0.4× 121 1.5k
Xin Wu China 18 1.3k 0.9× 491 0.7× 975 1.5× 282 0.7× 636 1.8× 61 2.4k
Amit Banerjee United States 18 618 0.4× 254 0.4× 414 0.6× 252 0.7× 172 0.5× 75 1.4k
Xianghai Cao China 21 1.2k 0.9× 736 1.0× 455 0.7× 273 0.7× 132 0.4× 50 1.6k
Jihao Yin China 18 690 0.5× 267 0.4× 456 0.7× 233 0.6× 203 0.6× 89 1.6k

Countries citing papers authored by Heesung Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Heesung Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heesung Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Heesung Kwon. A scholar is included among the top collaborators of Heesung Kwon 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 Heesung Kwon. Heesung Kwon 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.
Lee, Hyungtae, et al.. (2024). UAV-Sim: NeRF-based Synthetic Data Generation for UAV-based Perception. 5323–5329. 3 indexed citations
2.
Lee, Hyungtae, Yan Zhang, Heesung Kwon, & Shuvra S. Bhattacharyya. (2024). Exploring the Potential of Synthetic Data to Replace Real Data. 1005–1011.
3.
Lee, Hyungtae & Heesung Kwon. (2022). Self-Supervised Contrastive Learning for Cross-Domain Hyperspectral Image Representation. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 3239–3243. 14 indexed citations
4.
Lee, Hyungtae, Heesung Kwon, & Wonkook Kim. (2021). Generating Hard Examples for Pixel-Wise Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 9504–9517. 7 indexed citations
6.
Kwon, Heesung, et al.. (2019). Cooperative Learning for Multi-perspective Image Classification. 75–80. 2 indexed citations
7.
Lee, Hyungtae, Sungmin Eum, & Heesung Kwon. (2018). Going deeper with CNN in malicious crowd event classification. 41–41. 1 indexed citations
8.
Lee, Hyungtae, et al.. (2016). Joint Deep Exploitation of Semantic Keywords and Visual Features for Malicious Crowd Image Classification.. arXiv (Cornell University). 1 indexed citations
9.
Gurram, Prudhvi, Heesung Kwon, & Charles E. Davidson. (2016). Coalition Game Theory-Based Feature Subspace Selection for Hyperspectral Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9(6). 2354–2364. 7 indexed citations
10.
Riggan, Benjamin S., et al.. (2016). Estimation of visible spectrum faces from polarimetric thermal faces. 1–7. 18 indexed citations
11.
Gurram, Prudhvi & Heesung Kwon. (2012). Kernel-based joint spectral and spatial exploitation using Hilbert space embedding for hyperspectral classification. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8390. 83901R–83901R. 2 indexed citations
12.
Gurram, Prudhvi & Heesung Kwon. (2012). Sparse Kernel-Based Ensemble Learning With Fully Optimized Kernel Parameters for Hyperspectral Classification Problems. IEEE Transactions on Geoscience and Remote Sensing. 51(2). 787–802. 24 indexed citations
13.
Nasrabadi, Nasser M., et al.. (2006). Locating mines in SAR imagery using change detection methods. International Conference on Signal Processing. 24–29.
14.
Kwon, Heesung, et al.. (2006). Kernel matched subspace detectors for hyperspectral target detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(2). 178–194. 114 indexed citations
15.
Kwon, Heesung & Nasser M. Nasrabadi. (2005). Hyperspectral target detection using kernel orthogonal subspace projection. II–702. 4 indexed citations
16.
Kwon, Heesung & Nasser M. Nasrabadi. (2005). Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing. 43(2). 388–397. 638 indexed citations breakdown →
17.
Kwon, Heesung, et al.. (2004). Automated vehicle detection in forward-looking infrared imagery. Applied Optics. 43(2). 333–333. 17 indexed citations
18.
Kwon, Heesung, et al.. (2002). Very low bit rate video codec using variable blocksize entropy-constrained residual vector quantization. 2. 1460–1463. 1 indexed citations
19.
Kwon, Heesung, et al.. (2001). Multisensor target detection using adaptive feature-based fusion. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4379. 112–112. 1 indexed citations
20.
Kwon, Heesung, et al.. (1997). Very low bit-rate video coding using variable block-size entropy-constrained residual vector quantizers. IEEE Journal on Selected Areas in Communications. 15(9). 1714–1725. 3 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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