Seunghwan Park

44 papers receiving 320 citations

Peers

Seunghwan Park
Comparison fields: 5 of 85
  • Electrical and Electronic Engineering 136
  • Materials Chemistry 72
  • Artificial Intelligence 62
  • Computer Vision and Pattern Recognition 45
  • Biomedical Engineering 43
Replace Chih-Hung Liu with:
Chih-Hung Liu Taiwan
Xiaolong Xie China
Liwen Chen China
Poonam Singh India
Xiaoling Ye China
Zhao-Qian Chen China
Haonan Wang China
Tran Trong Dao Vietnam
A. Annamalai United States
Seunghwan Park relative to Chih-Hung Liu Taiwan Chih-Hung Liu's profile →
Citations per field
00.5×4.4×
Chih-Hung Liu · 1×
Citations per year

Countries citing papers authored by Seunghwan Park

Since Specialization
Citations

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

Fields of papers citing papers by Seunghwan Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seunghwan Park

This figure shows the co-authorship network connecting the top 25 collaborators of Seunghwan Park. A scholar is included among the top collaborators of Seunghwan Park 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 Seunghwan Park. Seunghwan Park 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
#WorkIndexed citations
1 0
2 0
3 1
4 2
5 3
6 4
7 6
8 79
9 15
10 9
11 1
12
Small Area Estimation Combining Information from Several Sources
8
13
The response of visual and verbal information in advertising design -focused on fMRI
2
14 0
15 5
16 3
17
Local Appearance-based Face Recognition Using SVM and PCA
0
18
A New Analytical Representation to Robot Path Generation with Collision Avoidance through the Use of the Collision Map
13
19 9
20 12

About Seunghwan Park

Seunghwan Park is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Aerospace Engineering, having authored 50 papers that have together received 342 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (12 papers), Robotic Path Planning Algorithms (9 papers) and Robotics and Automated Systems (6 papers). The work is most often cited by research in Electrochemistry (22 citations), Statistics and Probability (25 citations) and Electrical and Electronic Engineering (136 citations). Seunghwan Park has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Kwangsu Lee, Kyung-Min Yeon, Jungbae Kim, Dong Hoon Lee, Jae Kwang Kim, Beom-Hee Lee, Jiho Chang, Beom Hee Lee, Gon-Woo Kim and Takafumi Yao. Their work appears in journals such as Expert Systems with Applications, Psychological Medicine and Biosensors and Bioelectronics.

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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