Sung-Hoon Yoon

24 papers receiving 548 citations

Peers

Sung-Hoon Yoon
Comparison fields: 5 of 84
  • Biomaterials 186
  • Computer Vision and Pattern Recognition 140
  • Building and Construction 92
  • Biomedical Engineering 277
  • Artificial Intelligence 112
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Citations per year

Countries citing papers authored by Sung-Hoon Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Sung-Hoon Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sung-Hoon Yoon. 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 Sung-Hoon Yoon. The network helps show where Sung-Hoon Yoon may publish in the future.

Co-authors

The 25 scholars most cited alongside Sung-Hoon Yoon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sung-Hoon Yoon Line = papers co-authored together Sung-Hoon Yoon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202191
2 200886
3 200877
4 202153
5 202340
6 201238
7 201938
8 201131
9 201030
10
The fate of hexenuronic acid groups during kraft pulping of hardwoods
200125
11 201218
12
The fate of hexenuronic acid groups during alkaline pulping of loblolly pine
200117
13 201015
14 19878
15 20217
16
An integrative approach: Environmental quality (EQ) evaluation in residential buildings.
20084
17 20114
18 20063
19 20193
20 20211

About Sung-Hoon Yoon

Sung-Hoon Yoon is a scholar working on Biomedical Engineering, Biomaterials, Building and Construction, Computer Vision and Pattern Recognition and Food Science, having authored 32 papers that have together received 595 indexed citations. Recurring topics across this work include Lignin and Wood Chemistry (9 papers), Advanced Cellulose Research Studies (5 papers), Biofuel production and bioconversion (5 papers), Energy and Environmental Systems (3 papers), Sustainable Building Design and Assessment (2 papers), Adversarial Robustness in Machine Learning (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Biomaterials (186 citations), Computer Vision and Pattern Recognition (140 citations), Building and Construction (92 citations), Biomedical Engineering (277 citations) and Artificial Intelligence (112 citations). Sung-Hoon Yoon has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Adriaan van Heiningen, Kuk‐Jin Yoon, Hyeonseong Kim, J. Y. Zhu, Xin‐Sheng Chai, Tae‐Kyun Kim, Lin Wang, Mehmet Sefik Tunc, Taeyeon Kim and Kyungmo Kang. Their work appears in journals such as TAPPI Journal, Journal of Industrial and Engineering Chemistry, Journal of Asian Architecture and Building Engineering, Industrial & Engineering Chemistry Research and Journal of Materials Science.

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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