Jaeseok Yun

6.1k total citations
46 papers, 1.5k citations indexed

About

Jaeseok Yun is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Jaeseok Yun has authored 46 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 19 papers in Electrical and Electronic Engineering and 16 papers in Computer Networks and Communications. Recurrent topics in Jaeseok Yun's work include Context-Aware Activity Recognition Systems (18 papers), IoT and Edge/Fog Computing (14 papers) and IoT-based Smart Home Systems (8 papers). Jaeseok Yun is often cited by papers focused on Context-Aware Activity Recognition Systems (18 papers), IoT and Edge/Fog Computing (14 papers) and IoT-based Smart Home Systems (8 papers). Jaeseok Yun collaborates with scholars based in South Korea, United States and United Kingdom. Jaeseok Yun's co-authors include Jaeho Kim, Sang‐Shin Lee, Jaiyong Lee, Jae-Woo Kim, Min-Woo Ryu, Sung-Chan Choi, Jiyoung Woo, Daehee Kim, Dong Min Kim and Martin Bauer and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, IEEE Access and IEEE Communications Magazine.

In The Last Decade

Jaeseok Yun

39 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaeseok Yun South Korea 21 698 605 331 274 179 46 1.5k
Nagender Kumar Suryadevara New Zealand 19 937 1.3× 951 1.6× 642 1.9× 291 1.1× 198 1.1× 45 2.2k
Bruno Silva South Africa 17 1.3k 1.9× 881 1.5× 162 0.5× 261 1.0× 153 0.9× 75 2.2k
Biljana Risteska Stojkoska North Macedonia 14 518 0.7× 637 1.1× 271 0.8× 108 0.4× 213 1.2× 33 1.3k
Ahmed Abdelgawad United States 24 529 0.8× 620 1.0× 250 0.8× 170 0.6× 252 1.4× 118 1.9k
Kumar Yelamarthi United States 22 484 0.7× 395 0.7× 153 0.5× 282 1.0× 185 1.0× 113 1.5k
Waheb A. Jabbar Malaysia 19 856 1.2× 693 1.1× 121 0.4× 139 0.5× 107 0.6× 74 1.6k
Ivanovitch Silva Brazil 21 455 0.7× 704 1.2× 297 0.9× 182 0.7× 130 0.7× 121 1.6k
Lama Nachman United States 21 594 0.9× 677 1.1× 277 0.8× 221 0.8× 151 0.8× 59 1.8k
Ramón Sanchez‐Iborra Spain 21 875 1.3× 839 1.4× 182 0.5× 200 0.7× 113 0.6× 63 1.5k
Petar Šolić Croatia 21 1.1k 1.6× 682 1.1× 140 0.4× 156 0.6× 276 1.5× 100 2.2k

Countries citing papers authored by Jaeseok Yun

Since Specialization
Citations

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

Fields of papers citing papers by Jaeseok Yun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaeseok Yun

This figure shows the co-authorship network connecting the top 25 collaborators of Jaeseok Yun. A scholar is included among the top collaborators of Jaeseok Yun 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 Jaeseok Yun. Jaeseok Yun 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.
Chen, Jianhua, Peilin Li, Bing Zhang, et al.. (2025). A Comprehensive Review of Artificial Intelligence-Based Algorithms for Predicting the Remaining Useful Life of Equipment. PubMed Central. 25(14). 4481–4481. 1 indexed citations
2.
3.
Yun, Jaeseok, et al.. (2024). Enhancing atrial fibrillation classification from single-lead electrocardiogram signals using attention-based networks and generative adversarial networks with density-based clustering. Engineering Applications of Artificial Intelligence. 133. 108607–108607. 6 indexed citations
4.
Yun, Jaeseok, et al.. (2024). Negative Emotion Recognition Using PPG Wearable Devices and Machine Learning. KIISE Transactions on Computing Practices. 30(6). 253–263.
5.
Yun, Jaeseok, et al.. (2024). IoT-driven wearable devices enhancing healthcare: ECG classification with cluster-based GAN and meta-features. Internet of Things. 28. 101405–101405. 6 indexed citations
6.
Yun, Jaeseok, et al.. (2022). Are You Wearing a Mask? Detecting If a Person Wears a Mask Using a Wristband. Sensors. 22(5). 1745–1745.
7.
Woo, Jiyoung & Jaeseok Yun. (2019). Detection of Moving Direction using PIR Sensors and Deep Learning Algorithm. Journal of the Korea Society of Computer and Information. 24(3). 11–17. 1 indexed citations
8.
Yun, Jaeseok & Jiyoung Woo. (2019). A Comparative Analysis of Deep Learning and Machine Learning on Detecting Movement Directions Using PIR Sensors. IEEE Internet of Things Journal. 7(4). 2855–2868. 39 indexed citations
9.
Yun, Jaeseok, et al.. (2017). Dynamic Service Composition and Development Using Heterogeneous IoT Systems. Journal of the Korea Society of Computer and Information. 22(9). 91–97. 1 indexed citations
10.
Sung, Nak-Myoung & Jaeseok Yun. (2017). Medication Reminder System for Smart Aging Services Using IoT Platforms and Products. Journal of the Korea Society of Computer and Information. 22(9). 107–113. 3 indexed citations
11.
Yun, Jaeseok, et al.. (2016). Interworking of oneM2M-based IoT systems and legacy systems for consumer products. 423–428. 21 indexed citations
12.
Kim, Jaeho, Jaeseok Yun, Sung-Chan Choi, et al.. (2016). Standard-based IoT platforms interworking: implementation, experiences, and lessons learned. IEEE Communications Magazine. 54(7). 48–54. 67 indexed citations
13.
Kim, Jaeho, et al.. (2016). Towards the oneM2M standards for building IoT ecosystem: Analysis, implementation and lessons. Peer-to-Peer Networking and Applications. 11(1). 139–151. 16 indexed citations
14.
Ryu, Min-Woo, et al.. (2015). Design and implementation of a connected farm for smart farming system. 1–4. 108 indexed citations
15.
Yun, Jaeseok, Sung-Chan Choi, Nak-Myoung Sung, & Jaeho Kim. (2015). Demo. 473–474. 2 indexed citations
16.
Ryu, Min-Woo, Jaeho Kim, & Jaeseok Yun. (2015). Integrated Semantics Service Platform for the Internet of Things: A Case Study of a Smart Office. Sensors. 15(1). 2137–2160. 60 indexed citations
17.
Yun, Jaeseok & Sang‐Shin Lee. (2014). Human Movement Detection and Identification Using Pyroelectric Infrared Sensors. Sensors. 14(5). 8057–8081. 143 indexed citations
18.
Yun, Jaeseok, et al.. (2014). Detecting Direction of Movement Using Pyroelectric Infrared Sensors. IEEE Sensors Journal. 14(5). 1482–1489. 76 indexed citations
19.
Yun, Jaeseok, Gregory D. Abowd, Jeha Ryu, & Woontack Woo. (2008). USER IDENTIFICATION WITH USER'S STEPPING PATTERN OVER THE UBIFLOORII. International Journal of Pattern Recognition and Artificial Intelligence. 22(3). 497–514. 7 indexed citations
20.
Yun, Jaeseok, et al.. (2003). The User Identification System Using Walking Pattern over the ubiFloor. 제어로봇시스템학회 국제학술대회 논문집. 1046–1050. 30 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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