Yo‐Sung Ho

4.8k total citations
280 papers, 3.1k citations indexed

About

Yo‐Sung Ho is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology. According to data from OpenAlex, Yo‐Sung Ho has authored 280 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 271 papers in Computer Vision and Pattern Recognition, 89 papers in Signal Processing and 74 papers in Media Technology. Recurrent topics in Yo‐Sung Ho's work include Advanced Vision and Imaging (175 papers), Video Coding and Compression Technologies (85 papers) and Advanced Image Processing Techniques (75 papers). Yo‐Sung Ho is often cited by papers focused on Advanced Vision and Imaging (175 papers), Video Coding and Compression Technologies (85 papers) and Advanced Image Processing Techniques (75 papers). Yo‐Sung Ho collaborates with scholars based in South Korea, China and United States. Yo‐Sung Ho's co-authors include Feng Shao, Kwan‐Jung Oh, Qiuping Jiang, Gangyi Jiang, Sung Yeol Kim, Sehoon Yea, Sang-Kwang Lee, Mei Yu, Xiongli Chai and Young‐Ho Suh and has published in prestigious journals such as IEEE Transactions on Image Processing, Optics Express and Expert Systems with Applications.

In The Last Decade

Yo‐Sung Ho

263 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yo‐Sung Ho South Korea 26 2.8k 776 718 221 181 280 3.1k
Shang‐Hong Lai Taiwan 28 2.5k 0.9× 456 0.6× 454 0.6× 97 0.4× 243 1.3× 230 3.2k
Gangyi Jiang China 31 3.7k 1.3× 896 1.2× 1.5k 2.1× 96 0.4× 92 0.5× 331 4.2k
Sifei Liu United States 19 2.8k 1.0× 619 0.8× 466 0.6× 183 0.8× 112 0.6× 49 3.2k
Hongliang Li China 35 4.1k 1.5× 728 0.9× 1.1k 1.5× 55 0.2× 200 1.1× 215 4.5k
Björn Stenger Japan 28 2.4k 0.9× 178 0.2× 484 0.7× 146 0.7× 235 1.3× 86 3.0k
Huanqiang Zeng China 29 2.2k 0.8× 502 0.6× 545 0.8× 107 0.5× 117 0.6× 157 2.6k
Jörn Östermann Germany 27 2.5k 0.9× 1.5k 1.9× 161 0.2× 195 0.9× 155 0.9× 205 3.5k
Kwanghoon Sohn South Korea 31 3.1k 1.1× 278 0.4× 1.1k 1.6× 57 0.3× 414 2.3× 227 3.6k
Lap‐Pui Chau Singapore 31 3.5k 1.3× 1.5k 2.0× 639 0.9× 129 0.6× 86 0.5× 196 3.9k
Sang Uk Lee South Korea 24 2.1k 0.8× 470 0.6× 329 0.5× 104 0.5× 387 2.1× 167 2.8k

Countries citing papers authored by Yo‐Sung Ho

Since Specialization
Citations

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

Fields of papers citing papers by Yo‐Sung Ho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yo‐Sung Ho. 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 Yo‐Sung Ho. The network helps show where Yo‐Sung Ho may publish in the future.

Co-authorship network of co-authors of Yo‐Sung Ho

This figure shows the co-authorship network connecting the top 25 collaborators of Yo‐Sung Ho. A scholar is included among the top collaborators of Yo‐Sung Ho 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 Yo‐Sung Ho. Yo‐Sung Ho 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.
Shao, Feng, et al.. (2024). BGDFNet: Bidirectional Gated and Dynamic Fusion Network for RGB-T Crowd Counting in Smart City System. IEEE Transactions on Instrumentation and Measurement. 73. 1–16. 9 indexed citations
2.
Chen, Yeyao, et al.. (2024). HDR light field imaging of dynamic scenes: A learning-based method and a benchmark dataset. Pattern Recognition. 150. 110313–110313. 8 indexed citations
3.
Shao, Feng, et al.. (2024). Visual Prompt Multibranch Fusion Network for RGB-Thermal Crowd Counting. IEEE Internet of Things Journal. 11(19). 31758–31775. 9 indexed citations
4.
Shao, Feng, et al.. (2023). Hallucinated-PQA: No reference point cloud quality assessment via injecting pseudo-reference features. Expert Systems with Applications. 243. 122953–122953. 7 indexed citations
5.
Zhang, Yun, et al.. (2021). Projection Invariant Feature and Visual Saliency-Based Stereoscopic Omnidirectional Image Quality Assessment. IEEE Transactions on Broadcasting. 67(2). 512–523. 19 indexed citations
6.
Yu, Mei, et al.. (2020). Pseudo Video and Refocused Images-Based Blind Light Field Image Quality Assessment. IEEE Transactions on Circuits and Systems for Video Technology. 31(7). 2575–2590. 31 indexed citations
7.
Huang, Chao, Zongju Peng, Yong Xu, et al.. (2020). Online Learning-Based Multi-Stage Complexity Control for Live Video Coding. IEEE Transactions on Image Processing. 30. 641–656. 21 indexed citations
8.
Jiang, Qiuping, Wei Gao, Shiqi Wang, et al.. (2020). Blind Image Quality Measurement by Exploiting High-Order Statistics With Deep Dictionary Encoding Network. IEEE Transactions on Instrumentation and Measurement. 69(10). 7398–7410. 37 indexed citations
9.
Shao, Feng, Yan Yang, Qiuping Jiang, Gangyi Jiang, & Yo‐Sung Ho. (2017). Automated Quality Assessment of Fundus Images via Analysis of Illumination, Naturalness and Structure. IEEE Access. 6. 806–817. 28 indexed citations
10.
Ho, Yo‐Sung, et al.. (2011). High-resolution Depth Generation using Multi-view Camera and Time-of-Flight Depth Camera. Journal of the Institute of Electronics Engineers of Korea. 48(6). 1–7.
11.
Ho, Yo‐Sung, et al.. (2010). Carved Visual Hull using Correlation of Projected Pixels. ICEIC : International Conference on Electronics, Informations and Communications. 309–312. 1 indexed citations
12.
Ho, Yo‐Sung, et al.. (2009). Color-compensated Stereo Matching Algorithm for Color Inconsistent Stereo Pair. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 717–720. 1 indexed citations
13.
Ho, Yo‐Sung, et al.. (2009). View Synthesis using Depth Map for 3D Video. Hokkaido University Collection of Scholarly and Academic Papers (Hokkaido University). 350–357. 7 indexed citations
14.
Ho, Yo‐Sung, Sung Yeol Kim, & Eun‐Kyung Lee. (2008). Three-dimensional Video Generation for Realistic Broadcasting Services. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 1839–1842. 6 indexed citations
15.
Ho, Yo‐Sung, et al.. (2008). Multi-view Depth Map Estimation Enhancing Temporal Consistency. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 29–32. 5 indexed citations
16.
Ho, Yo‐Sung, et al.. (2008). Geometrical compensation for multi-view video in multiple camera array. International Symposium ELMAR. 1. 83–86. 13 indexed citations
17.
Ho, Yo‐Sung, et al.. (2007). Quantization Parameter Selection Method For H.264-based Multi-view Video Coding. The Journal of Korean Institute of Communications and Information Sciences. 32. 579–584. 1 indexed citations
18.
Kim, Sung Yeol, et al.. (2007). Stereo Matching Using Global and Local Segmentation. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 1278–1279. 3 indexed citations
19.
Oh, Kwan‐Jung, Manbae Kim, JongWon Kim, et al.. (2007). Multi-View Video and Multi-Channel Audio Broadcasting System. 1–4. 8 indexed citations
20.
Woo, Woontack, et al.. (2006). Using Context Information to Improve Retrieval Accuracy in Content-Based Image Retrieval Systems. International Conference on Human-Computer Interaction. 926–930. 1 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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