Seung‐Hwan Bae

1.1k total citations
28 papers, 788 citations indexed

About

Seung‐Hwan Bae is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Seung‐Hwan Bae has authored 28 papers receiving a total of 788 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 5 papers in Aerospace Engineering. Recurrent topics in Seung‐Hwan Bae's work include Advanced Neural Network Applications (10 papers), Video Surveillance and Tracking Methods (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Seung‐Hwan Bae is often cited by papers focused on Advanced Neural Network Applications (10 papers), Video Surveillance and Tracking Methods (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Seung‐Hwan Bae collaborates with scholars based in South Korea and United States. Seung‐Hwan Bae's co-authors include Kuk‐Jin Yoon, Yongsang Yoo, Hyun Kim, Jongyoul Park, Hyuk‐Jae Lee, Paul Coddington, Jinkyu Lee, Ju Hong Yoon, Vladimir Shin and Seongkeun Park and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Seung‐Hwan Bae

26 papers receiving 771 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seung‐Hwan Bae South Korea 10 647 211 139 94 92 28 788
Bin Yan China 12 606 0.9× 89 0.4× 192 1.4× 71 0.8× 100 1.1× 50 787
Jack Sim United States 7 480 0.7× 158 0.7× 92 0.7× 45 0.5× 31 0.3× 12 710
M. Gorgoń Poland 15 338 0.5× 132 0.6× 54 0.4× 157 1.7× 20 0.2× 51 583
Renshu Gu China 10 423 0.7× 96 0.5× 74 0.5× 31 0.3× 40 0.4× 39 529
Jiaolong Xu Spain 13 681 1.1× 210 1.0× 131 0.9× 81 0.9× 172 1.9× 26 887
Xiaolong Jiang China 11 522 0.8× 264 1.3× 34 0.2× 31 0.3× 78 0.8× 30 655
Chengtao Cai China 14 357 0.6× 61 0.3× 159 1.1× 54 0.6× 43 0.5× 106 649
Tackgeun You South Korea 4 532 0.8× 207 1.0× 72 0.5× 47 0.5× 78 0.8× 4 661
Ju Jia Zou Australia 15 375 0.6× 90 0.4× 46 0.3× 56 0.6× 40 0.4× 52 693
Joon Hee Han South Korea 14 715 1.1× 111 0.5× 102 0.7× 24 0.3× 34 0.4× 43 874

Countries citing papers authored by Seung‐Hwan Bae

Since Specialization
Citations

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

Fields of papers citing papers by Seung‐Hwan Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung‐Hwan Bae. 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 Seung‐Hwan Bae. The network helps show where Seung‐Hwan Bae may publish in the future.

Co-authorship network of co-authors of Seung‐Hwan Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Seung‐Hwan Bae. A scholar is included among the top collaborators of Seung‐Hwan Bae 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 Seung‐Hwan Bae. Seung‐Hwan Bae 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.
Bae, Seung‐Hwan, et al.. (2025). Neural-NGBoost: Natural gradient boosting with neural network base learners. ICT Express. 11(5). 974–980.
2.
Shin, Hyun‐Chool, et al.. (2025). Region-aware knowledge distillation between monocular camera-based 3D object detectors. ICT Express. 11(4). 696–702. 1 indexed citations
3.
Bae, Seung‐Hwan, Hyuk‐Jae Lee, & Hyun Kim. (2024). MCM-SR: Multiple Constant Multiplication-Based CNN Streaming Hardware Architecture for Super-Resolution. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 33(1). 75–87.
4.
Bae, Seung‐Hwan, et al.. (2023). A New Approach to Lidar and Camera Fusion for Autonomous Driving. 751–753. 3 indexed citations
5.
Bae, Seung‐Hwan, et al.. (2023). AFI-GAN: Improving feature interpolation of feature pyramid networks via adversarial training for object detection. Pattern Recognition. 138. 109365–109365. 7 indexed citations
6.
Bae, Seung‐Hwan. (2023). Deformable Part Region Learning and Feature Aggregation Tree Representation for Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(9). 10817–10834. 12 indexed citations
7.
Bae, Seung‐Hwan, et al.. (2022). Effective Multi-Object Tracking via Global Object Models and Object Constraint Learning. Sensors. 22(20). 7943–7943. 5 indexed citations
8.
Bae, Seung‐Hwan. (2022). Deformable Part Region Learning for Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 95–103. 5 indexed citations
9.
Bae, Seung‐Hwan, Hyuk‐Jae Lee, & Hyun Kim. (2021). Cache Compression with Golomb-Rice Code and Quantization for Convolutional Neural Networks. 1–5. 4 indexed citations
10.
Yoo, Yongsang, et al.. (2020). Generative Adversarial Ensemble Learning for Face Forensics. IEEE Access. 8. 45421–45431. 25 indexed citations
11.
Bae, Seung‐Hwan. (2019). Object Detection Based on Region Decomposition and Assembly. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 8094–8101. 22 indexed citations
12.
Yoo, Yongsang, et al.. (2019). Adversarial Learning With Knowledge of Image Classification for Improving GANs. IEEE Access. 7. 56591–56605. 6 indexed citations
13.
Bae, Seung‐Hwan, et al.. (2018). Learning Discriminative Appearance Models for Online Multi-Object Tracking With Appearance Discriminability Measures. IEEE Access. 6. 67316–67328. 29 indexed citations
14.
Bae, Seung‐Hwan. (2018). Survey of amplitude‐aided multi‐target tracking methods. IET Radar Sonar & Navigation. 13(2). 243–253. 6 indexed citations
15.
Bae, Seung‐Hwan, et al.. (2016). Multi-Classifier-Based Automatic Polyp Detection in Endoscopic Images. Journal of Medical and Biological Engineering. 36(6). 871–882. 5 indexed citations
16.
Bae, Seung‐Hwan & Kuk‐Jin Yoon. (2015). Polyp Detection via Imbalanced Learning and Discriminative Feature Learning. IEEE Transactions on Medical Imaging. 34(11). 2379–2393. 78 indexed citations
17.
Bae, Seung‐Hwan & Kuk‐Jin Yoon. (2014). Robust Online Multiobject Tracking With Data Association and Track Management. IEEE Transactions on Image Processing. 23(7). 2820–2833. 32 indexed citations
18.
Bae, Seung‐Hwan & Kuk‐Jin Yoon. (2014). Robust Online Multi-object Tracking Based on Tracklet Confidence and Online Discriminative Appearance Learning. 1218–1225. 281 indexed citations
19.
Bae, Seung‐Hwan, et al.. (2012). Automated multi-target tracking with kinematic and non-kinematic information. IET Radar Sonar & Navigation. 6(4). 272–281. 6 indexed citations
20.
Bae, Seung‐Hwan, et al.. (1995). PARALLEL WOLFF CLUSTER ALGORITHMS. International Journal of Modern Physics C. 6(2). 197–210. 6 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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