Do Hyoung Shin

1.1k total citations
43 papers, 802 citations indexed

About

Do Hyoung Shin is a scholar working on Civil and Structural Engineering, Building and Construction and Computer Vision and Pattern Recognition. According to data from OpenAlex, Do Hyoung Shin has authored 43 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Civil and Structural Engineering, 12 papers in Building and Construction and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Do Hyoung Shin's work include Structural Health Monitoring Techniques (11 papers), Infrastructure Maintenance and Monitoring (10 papers) and BIM and Construction Integration (9 papers). Do Hyoung Shin is often cited by papers focused on Structural Health Monitoring Techniques (11 papers), Infrastructure Maintenance and Monitoring (10 papers) and BIM and Construction Integration (9 papers). Do Hyoung Shin collaborates with scholars based in South Korea and United States. Do Hyoung Shin's co-authors include Phillip S. Dunston, Seunghoo Jeong, Seungjun Kim, Sung‐Han Sim, Won‐Suk Jang, Sangwook Lee, Sangyoub Lee, Han‐Soo Kim, Xiangyu Wang and Hung Soo Kim and has published in prestigious journals such as Sensors, Automation in Construction and Human Genetics.

In The Last Decade

Do Hyoung Shin

42 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Do Hyoung Shin South Korea 16 250 223 221 148 84 43 802
Vahid Balali United States 16 201 0.8× 216 1.0× 213 1.0× 166 1.1× 143 1.7× 42 829
Min Hu China 20 264 1.1× 204 0.9× 418 1.9× 78 0.5× 36 0.4× 74 1.3k
Faridaddin Vahdatikhaki Netherlands 16 265 1.1× 543 2.4× 72 0.3× 129 0.9× 115 1.4× 60 1.1k
Meng‐Han Tsai Taiwan 18 147 0.6× 431 1.9× 212 1.0× 268 1.8× 210 2.5× 45 1.1k
Ali Motamedi Canada 22 245 1.0× 775 3.5× 173 0.8× 388 2.6× 115 1.4× 83 1.7k
Cheng Zhang China 22 356 1.4× 907 4.1× 123 0.6× 157 1.1× 179 2.1× 114 1.6k
Milad Memarzadeh United States 15 318 1.3× 132 0.6× 63 0.3× 93 0.6× 33 0.4× 40 830
Nipesh Pradhananga United States 16 318 1.3× 418 1.9× 56 0.3× 121 0.8× 141 1.7× 43 992
Seongdeok Bang South Korea 12 630 2.5× 127 0.6× 128 0.6× 156 1.1× 21 0.3× 18 918
Zhigang Shen United States 18 294 1.2× 424 1.9× 147 0.7× 139 0.9× 124 1.5× 63 992

Countries citing papers authored by Do Hyoung Shin

Since Specialization
Citations

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

Fields of papers citing papers by Do Hyoung Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Do Hyoung Shin. 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 Do Hyoung Shin. The network helps show where Do Hyoung Shin may publish in the future.

Co-authorship network of co-authors of Do Hyoung Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Do Hyoung Shin. A scholar is included among the top collaborators of Do Hyoung Shin 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 Do Hyoung Shin. Do Hyoung Shin 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.
Shin, Do Hyoung, et al.. (2023). Small Tool Image Database and Object Detection Approach for Indoor Construction Site Safety. KSCE Journal of Civil Engineering. 27(3). 930–939. 9 indexed citations
2.
Shin, Do Hyoung, et al.. (2023). Improved Discriminative Object Localization Algorithm for Safety Management of Indoor Construction. Sensors. 23(8). 3870–3870. 2 indexed citations
3.
Kim, Seungjun, et al.. (2021). Damage detection of catenary mooring line based on recurrent neural networks. Ocean Engineering. 227. 108898–108898. 39 indexed citations
4.
Kim, Seungjun, et al.. (2020). Detection of damaged mooring line based on deep neural networks. Ocean Engineering. 209. 107522–107522. 36 indexed citations
5.
Shin, Do Hyoung, et al.. (2019). Generative Model of Acceleration Data for Deep Learning-based Damage Detection for Bridges Using Generative Adversarial Network. 9(1). 42–51. 5 indexed citations
6.
Jeong, Seunghoo, Young‐Joo Lee, Do Hyoung Shin, & Sung‐Han Sim. (2019). Automated Real-Time Assessment of Stay-Cable Serviceability Using Smart Sensors. Applied Sciences. 9(20). 4469–4469. 7 indexed citations
7.
Jeong, Seunghoo, Eun‐Jin Kim, Do Hyoung Shin, Jong‐Woong Park, & Sung‐Han Sim. (2019). Data fusion-based damage identification for a monopile offshore wind turbine structure using wireless smart sensors. Ocean Engineering. 195. 106728–106728. 23 indexed citations
8.
Kim, Hanbeen, et al.. (2019). Forecasting Short-Term Housing Transaction Volumes using Time-Series and Internet Search Queries. KSCE Journal of Civil Engineering. 23(6). 2409–2416. 8 indexed citations
9.
Shin, Soobong, et al.. (2018). Numerical Model Updating for Bridge Maintenance Using Digital-Twin Model. 8(4). 34–40. 4 indexed citations
10.
Shin, Do Hyoung, et al.. (2016). Home sales index prediction model based on cluster and principal component statistical approaches in a big data analytic concept. KSCE Journal of Civil Engineering. 21(1). 67–75. 3 indexed citations
11.
Shin, Do Hyoung, et al.. (2014). Identification of applications of mobile devices to improve airport BHS maintenance. KSCE Journal of Civil Engineering. 18(5). 1207–1212. 2 indexed citations
12.
Lee, Sangwook, et al.. (2014). Non-destructive testing methods in the U.S. for bridge inspection and maintenance. KSCE Journal of Civil Engineering. 18(5). 1322–1331. 54 indexed citations
13.
Shin, Do Hyoung, et al.. (2011). Hibrid Approach of Cameras and GPS for Displacement Measurements of Super Long-Sapn Bridges. Proceedings of the ... ISARC. 1 indexed citations
14.
Kwon, Oh Kyoung, et al.. (2010). The Integrated Management System (Fims) for the Four Major Rivers Restoration Project in South Korea. 956. 1 indexed citations
15.
Shin, Do Hyoung, et al.. (2008). CAMERA CONSTRAINT ON MULTI-RANGE CALIBRATION OF AUGMENTED REALITY SYSTEMS FOR CONSTRUCTION SITES. Journal of Information Technology in Construction. 13(32). 521–535. 4 indexed citations
16.
Shin, Do Hyoung & Phillip S. Dunston. (2008). Evaluation of Augmented Reality in steel column inspection. Automation in Construction. 18(2). 118–129. 80 indexed citations
17.
Shin, Do Hyoung & Phillip S. Dunston. (2008). Identification of application areas for Augmented Reality in industrial construction based on technology suitability. Automation in Construction. 17(7). 882–894. 122 indexed citations
18.
Shin, Do Hyoung, et al.. (2007). Large Scale Calibration for Augmented Reality on Construction Sites. Human Genetics. 81(2). 183–4. 1 indexed citations
19.
Shin, Do Hyoung, Phillip S. Dunston, & Xiangyu Wang. (2005). View changes in augmented reality computer-aided-drawing. ACM Transactions on Applied Perception. 2(1). 1–14. 13 indexed citations
20.
Wang, Xiangyu, Do Hyoung Shin, & Phillip S. Dunston. (2003). Issues in Mixed Reality-Based Design and Collaboration Environments. 1–9. 8 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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