Jeonghun Baek

985 total citations · 1 hit paper
11 papers, 369 citations indexed

About

Jeonghun Baek is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Jeonghun Baek has authored 11 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Jeonghun Baek's work include Natural Language Processing Techniques (4 papers), Handwritten Text Recognition Techniques (3 papers) and Social Robot Interaction and HRI (1 paper). Jeonghun Baek is often cited by papers focused on Natural Language Processing Techniques (4 papers), Handwritten Text Recognition Techniques (3 papers) and Social Robot Interaction and HRI (1 paper). Jeonghun Baek collaborates with scholars based in Japan, South Korea and Malaysia. Jeonghun Baek's co-authors include Sungrae Park, Junyeop Lee, Hwalsuk Lee, Geewook Kim, Dongyoon Han, Sangdoo Yun, Seong Joon Oh, Kiyoharu Aizawa, Yusuke Matsui and Ikuo Mizuuchi and has published in prestigious journals such as Journal of The Electrochemical Society, Chemical Engineering Journal and International Journal of Ophthalmology.

In The Last Decade

Jeonghun Baek

5 papers receiving 346 citations

Hit Papers

What Is Wrong With Scene Text Recognition Model Compariso... 2019 2026 2021 2023 2019 50 100 150 200 250
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. What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
    2019 296 citations Jeonghun Baek, Geewook Kim et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeonghun Baek Japan 4 311 113 90 15 13 11 369
Sungrae Park South Korea 2 265 0.9× 92 0.8× 77 0.9× 14 0.9× 12 0.9× 3 306
Geewook Kim Japan 4 262 0.8× 103 0.9× 78 0.9× 11 0.7× 12 0.9× 10 318
Chris Tensmeyer United States 7 205 0.7× 56 0.5× 32 0.4× 8 0.5× 6 0.5× 13 256
Zenghui Sun China 5 383 1.2× 108 1.0× 172 1.9× 7 0.5× 8 0.6× 7 425
Bailan Feng China 10 268 0.9× 54 0.5× 60 0.7× 3 0.2× 11 0.8× 32 314
Ayan Kumar Bhunia India 10 317 1.0× 100 0.9× 131 1.5× 4 0.3× 8 0.6× 17 390
Shangbang Long United States 4 267 0.9× 70 0.6× 112 1.2× 11 0.7× 17 1.3× 8 312
Lucas Pascotti Valem Brazil 9 213 0.7× 61 0.5× 41 0.5× 2 0.1× 15 1.2× 41 267
Byungju Kim South Korea 4 168 0.5× 137 1.2× 26 0.3× 5 0.3× 7 0.5× 5 279

Countries citing papers authored by Jeonghun Baek

Since Specialization
Citations

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

Fields of papers citing papers by Jeonghun Baek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeonghun Baek

This figure shows the co-authorship network connecting the top 25 collaborators of Jeonghun Baek. A scholar is included among the top collaborators of Jeonghun Baek 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 Jeonghun Baek. Jeonghun Baek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
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Baek, Jeonghun, Yusuke Matsui, & Kiyoharu Aizawa. (2024). Cross-Lingual Learning in Multilingual Scene Text Recognition. 6770–6774.
5.
Kim, Yong Il, Bumjin Kim, Jeonghun Baek, Jong-Huy Kim, & Jungjoon Yoo. (2022). Hybrid Aluminum-Ion Capacitor with High Energy Density and Long-Term Durability. Journal of The Electrochemical Society. 169(12). 120521–120521. 3 indexed citations
6.
Baek, Jeonghun, et al.. (2022). Comparison of vegetable oils on the uptake of lutein and zeaxanthin by ARPE-19 cells. International Journal of Ophthalmology. 16(1). 40–46.
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Baek, Jeonghun, Yusuke Matsui, & Kiyoharu Aizawa. (2021). What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels. 3112–3121. 55 indexed citations
9.
Baek, Youngmin, Dae‐Hyun Nam, Sungrae Park, et al.. (2020). CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks. 2404–2412. 10 indexed citations
10.
Baek, Jeonghun, Geewook Kim, Junyeop Lee, et al.. (2019). What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis. 4714–4722. 296 indexed citations breakdown →
11.
Baek, Jeonghun, et al.. (2014). A situation-aware action selection based on individual's preference using emotion estimation. 356–361. 5 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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