Kwanghoon Sohn

214 papers receiving 3.4k citations

Hit Papers

Fast Global Image Smoothing Based on Weighted Least Squares2014202620182022201450100150200250

Peers

Kwanghoon Sohn
Comparison fields: 5 of 127
  • Computer Vision and Pattern Recognition 3.1k
  • Media Technology 1.1k
  • Aerospace Engineering 414
  • Automotive Engineering 387
  • Artificial Intelligence 296
Replace Kuk‐Jin Yoon with:
Kuk‐Jin Yoon South Korea
Zejian Yuan China
Philipp Krähenbühl United States
Robert Laganière Canada
Cláudio R. Jung Brazil
Shengfeng He China
Ramakant Nevatia United States
Ioannis Pratikakis Greece
Zheng Zhu China
Caner Hazırbaş Germany
Kwanghoon Sohn relative to Kuk‐Jin Yoon South Korea Kuk‐Jin Yoon's profile →
Citations per field
00.5×2.7×
Kuk‐Jin Yoon · 1×
Citations per year

Countries citing papers authored by Kwanghoon Sohn

Since Specialization
Citations

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

Fields of papers citing papers by Kwanghoon Sohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kwanghoon Sohn

This figure shows the co-authorship network connecting the top 25 collaborators of Kwanghoon Sohn. A scholar is included among the top collaborators of Kwanghoon Sohn 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 Kwanghoon Sohn. Kwanghoon Sohn 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 2
4 3
5 2
6 51
7 16
8
Deep network for simultaneous stereo matching and dehazing
9
9 13
10
PARN: Pyramidal Affine Regression Networks for Dense Semantic Correspondence Estimation
4
11 108
12 11
13
Robot component connection mechanism using IP based permission assignment
1
14 84
15 9
16
Edge-directional technique for joint disparity-motion estimation of stereoscopic sequences
1
17 16
18
A 3D Head Pose Estimation for Face Recognition.
1
19
Region selective variable block size matching algorithm for video coding
0
20 26

About Kwanghoon Sohn

Kwanghoon Sohn is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 227 papers that have together received 3.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (94 papers), Advanced Image Processing Techniques (47 papers) and Image Enhancement Techniques (45 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.1k citations), Media Technology (1.1k citations) and Automotive Engineering (387 citations). Kwanghoon Sohn has collaborated with scholars based in South Korea, United States and Switzerland. Frequent co-authors include Dongbo Min, Seungryong Kim, Bumsub Ham, Hunjae Yoo, Youngjung Kim, Ki‐Hong Park, Donghyun Kim, Dongbo Min, N. Minh and Sung‐Hwan Choi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Expert Systems with Applications.

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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