M.-T. Sun

1.2k citations
25 papers · 911 indexed · h-index 13

M.-T. Sun

22 papers receiving 827 citations

Peers

M.-T. Sun
Comparison fields: 5 of 40
  • Signal Processing 681
  • Computer Vision and Pattern Recognition 706
  • Hardware and Architecture 75
  • Computational Theory and Mathematics 75
  • Artificial Intelligence 128
Replace Jiun-In Guo with:
Jiun-In Guo Taiwan
Jer Min Jou Taiwan
Tenkasi V. Ramabadran United States
Byeong Lee South Korea
H. Nussbaumer Switzerland
I. Kuroda Japan
E.V. Jones United Kingdom
Jau‐Yien Lee Taiwan
Glenn L. Cash United States
Mahesh Mehendale India
M.-T. Sun relative to Jiun-In Guo Taiwan Jiun-In Guo's profile →
Citations per field
00.5×1.5×2.1×
Jiun-In Guo · 1×
Citations per year

Countries citing papers authored by M.-T. Sun

Since Specialization
Citations

This map shows the geographic impact of M.-T. Sun'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 M.-T. Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.-T. Sun more than expected).

Fields of papers citing papers by M.-T. Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.-T. Sun. 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 M.-T. Sun. The network helps show where M.-T. Sun may publish in the future.

Co-authorship network

The 25 scholars most cited alongside M.-T. Sun, 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 M.-T. Sun Line = papers co-authored together M.-T. Sun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20101
4 200534
5 20045
6 20030
7 20033
8 20037
9 20031
10 200210
11 200127
12 200130
13
Special Issue on Segmentation, Description and Retrieval of Video Content
19988
14 199816
15 199240
16 199217
17 199112
18 1991140
19 1989247
20 198767

About M.-T. Sun

M.-T. Sun is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 25 papers that have together received 911 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (8 papers), Advanced Data Compression Techniques (7 papers), Digital Filter Design and Implementation (7 papers), Analog and Mixed-Signal Circuit Design (5 papers), Advanced Vision and Imaging (4 papers), Algorithms and Data Compression (4 papers), Image and Video Quality Assessment (3 papers) and Advancements in PLL and VCO Technologies (2 papers). The work is most often cited by research in Signal Processing (681 citations), Computer Vision and Pattern Recognition (706 citations) and Hardware and Architecture (75 citations). M.-T. Sun has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Long Wu, K.-M. Yang, Shawmin Lei, M.L. Liou, Supavadee Aramvith, Daniel Gática-Pérez, Zhuping Zhou, Salvador Ruíz-Correa, Kou-Hu Tzou and Hiroshi Fujiwara. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Image Processing, Proceedings of the IEEE, ACM Transactions on Multimedia Computing Communications and Applications and IEEE Transactions on Circuits and Systems.

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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