Hyung-Jeong Yang

4.4k total citations · 1 hit paper
190 papers, 2.8k citations indexed

About

Hyung-Jeong Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Hyung-Jeong Yang has authored 190 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Computer Vision and Pattern Recognition, 51 papers in Artificial Intelligence and 42 papers in Experimental and Cognitive Psychology. Recurrent topics in Hyung-Jeong Yang's work include Emotion and Mood Recognition (41 papers), Human Pose and Action Recognition (20 papers) and Image Retrieval and Classification Techniques (17 papers). Hyung-Jeong Yang is often cited by papers focused on Emotion and Mood Recognition (41 papers), Human Pose and Action Recognition (20 papers) and Image Retrieval and Classification Techniques (17 papers). Hyung-Jeong Yang collaborates with scholars based in South Korea, United States and Australia. Hyung-Jeong Yang's co-authors include Soo-Hyung Kim, Guee-Sang Lee, Christos Faloutsos, Jia-Yu Pan, Pınar Duygulu, Kyoung‐Yun Kim, Ngoc-Huynh Ho, Sun‐Hee Kim, In Seop Na and Min Jhon and has published in prestigious journals such as Applied Physics Letters, Expert Systems with Applications and IEEE Access.

In The Last Decade

Hyung-Jeong Yang

175 papers receiving 2.6k citations

Hit Papers

A Review of Machine Learning and Deep Learning Approaches... 2023 2026 2024 2025 2023 40 80 120
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.

  1. A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis
    2023 120 citations Soo-Hyung Kim, Min Jhon et al. Healthcare profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hyung-Jeong Yang South Korea 26 1.1k 833 522 255 239 190 2.8k
Zheru Chi Hong Kong 32 1.6k 1.5× 811 1.0× 314 0.6× 249 1.0× 200 0.8× 170 3.2k
Tomas Pfister United States 17 1.7k 1.6× 1.3k 1.5× 740 1.4× 151 0.6× 231 1.0× 52 3.0k
Soo-Hyung Kim South Korea 25 972 0.9× 597 0.7× 503 1.0× 183 0.7× 207 0.9× 232 2.3k
Jim Tørresen Norway 26 700 0.6× 739 0.9× 362 0.7× 249 1.0× 153 0.6× 211 2.7k
Fillia Makedon United States 29 1.1k 1.0× 911 1.1× 171 0.3× 374 1.5× 262 1.1× 302 4.0k
Jufeng Yang China 26 2.1k 1.9× 1.1k 1.4× 336 0.6× 277 1.1× 198 0.8× 100 3.4k
Ayan Seal India 34 1.4k 1.3× 470 0.6× 443 0.8× 403 1.6× 161 0.7× 79 2.8k
Chaitanya Ahuja United States 6 875 0.8× 1.1k 1.3× 271 0.5× 128 0.5× 299 1.3× 12 2.4k
Brian Lee Ireland 30 1.1k 1.0× 573 0.7× 156 0.3× 129 0.5× 203 0.8× 182 3.4k
Sicheng Zhao China 40 3.2k 2.9× 2.2k 2.7× 604 1.2× 372 1.5× 365 1.5× 162 5.6k

Countries citing papers authored by Hyung-Jeong Yang

Since Specialization
Citations

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

Fields of papers citing papers by Hyung-Jeong Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hyung-Jeong Yang. 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 Hyung-Jeong Yang. The network helps show where Hyung-Jeong Yang may publish in the future.

Co-authorship network of co-authors of Hyung-Jeong Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Hyung-Jeong Yang. A scholar is included among the top collaborators of Hyung-Jeong Yang 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 Hyung-Jeong Yang. Hyung-Jeong Yang 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.
Jhon, Min, et al.. (2025). A lightweight approach based on cross-modality for depression detection. Computers in Biology and Medicine. 186. 109618–109618. 1 indexed citations
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Yang, Hyung-Jeong, et al.. (2025). Multimodal Model for Automated Pain Assessment: Leveraging Video and fNIRS. Applied Sciences. 15(9). 5151–5151. 3 indexed citations
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Kim, Soo-Hyung, et al.. (2024). Temporal variational autoencoder model for in-hospital clinical emergency prediction. Biomedical Signal Processing and Control. 100. 106975–106975. 2 indexed citations
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Yang, Hyung-Jeong, et al.. (2024). Multi-horizon event detection for in-hospital clinical deterioration using dual-channel graph attention network. International Journal of Medical Informatics. 195. 105745–105745.
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Yang, Hyung-Jeong, et al.. (2024). Vector Quantized Diffusion Models for Multiple Appropriate Reactions Generation. 1–5. 2 indexed citations
10.
Yang, Hyung-Jeong, et al.. (2024). Explainable Deep Contrastive Federated Learning System for Early Prediction of Clinical Status in Intensive Care Unit. IEEE Access. 12. 117176–117202. 3 indexed citations
11.
Yang, Hyung-Jeong, et al.. (2024). A comparison between centralized and asynchronous federated learning approaches for survival outcome prediction using clinical and PET data from non-small cell lung cancer patients. Computer Methods and Programs in Biomedicine. 248. 108104–108104. 4 indexed citations
12.
Kim, Soo-Hyung, et al.. (2024). Effect of the Hand and Gaze Pointers in Remote Collaboration. IEEE Access. 12. 172774–172784. 3 indexed citations
13.
Kang, Sae‐Ryung, et al.. (2023). Survival Prediction Using Transformer-Based Categorical Feature Representation in the Treatment of Diffuse Large B-Cell Lymphoma. Healthcare. 11(8). 1171–1171. 3 indexed citations
14.
Yang, Hyung-Jeong, et al.. (2023). Robust Human Face Emotion Classification Using Triplet-Loss-Based Deep CNN Features and SVM. Sensors. 23(10). 4770–4770. 8 indexed citations
15.
Ho, Ngoc-Huynh, Hyung-Jeong Yang, Soo-Hyung Kim, Guee-Sang Lee, & Seok Bong Yoo. (2021). Deep Graph Fusion Based Multimodal Evoked Expressions From Large-Scale Videos. IEEE Access. 9. 127068–127080. 2 indexed citations
16.
Lee, Guee-Sang, et al.. (2019). Gesture-Based Emotion Recognition by 3D-CNN and LSTM with Keyframes Selection. International Journal of Contents. 15(4). 59–64. 3 indexed citations
17.
Lee, Guee-Sang, et al.. (2019). Continuous Hand Gesture Spotting and Classification Using 3D Finger Joints Information. 539–543. 12 indexed citations
18.
Na, In Seop, et al.. (2018). Multiple human tracking in drone image. Multimedia Tools and Applications. 78(4). 4563–4577. 13 indexed citations
19.
Yang, Hyung-Jeong, et al.. (2017). Real-Time Earthquake Detection Using Convolutional Neural Network and Social Data. 154–157. 15 indexed citations
20.
Tran, Tuan Anh, et al.. (2016). A mixture model using Random Rotation Bounding Box to detect table region in document image. Journal of Visual Communication and Image Representation. 39. 196–208. 12 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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