Ching‐Te Chiu

1.1k citations
68 papers · 800 · h-index 14

Impact in

Papers in

Ching‐Te Chiu

60 papers receiving 765 citations

Peers

Ching‐Te Chiu
Comparison fields: 5 of 87
  • Computer Vision and Pattern Recognition 419
  • Hardware and Architecture 91
  • Media Technology 89
  • Computer Networks and Communications 139
  • Signal Processing 56
Replace Sungpill Choi with:
Sungpill Choi South Korea
Ming‐Hwa Sheu Taiwan
Chao Zhu China
Jong Hwan Ko South Korea
Michel Paindavoine France
Karim Mohammadi Iran
Hengzhu Liu China
Sehoon Kim United States
Sek Chai United States
Ching‐Te Chiu relative to Sungpill Choi South Korea Sungpill Choi's profile →
Citations per field
00.5×2×2.6×
Sungpill Choi · 1×
Citations per year

Countries citing papers authored by Ching‐Te Chiu

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Te Chiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐Te Chiu. 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 Ching‐Te Chiu. The network helps show where Ching‐Te Chiu may publish in the future.

Co-authors

The 25 scholars most cited alongside Ching‐Te Chiu, 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 Ching‐Te Chiu Line = papers co-authored together Ching‐Te Chiu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019111
2 201981
3 201567
4 201162
5 201158
6 201946
7 201029
8 201028
9 201922
10 202219
11 202118
12 202017
13 201015
14 200714
15 201813
16 201111
17 200711
18 201510
19 201810
20 20179

About Ching‐Te Chiu

Ching‐Te Chiu is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Signal Processing, Media Technology and Computer Networks and Communications, having authored 68 papers that have together received 800 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (14 papers), Face and Expression Recognition (13 papers), Biometric Identification and Security (11 papers), Advanced Neural Network Applications (11 papers), Image Enhancement Techniques (11 papers), Human Pose and Action Recognition (9 papers), Face recognition and analysis (9 papers) and Advancements in PLL and VCO Technologies (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (419 citations), Hardware and Architecture (91 citations), Media Technology (89 citations), Computer Networks and Communications (139 citations) and Signal Processing (56 citations). Ching‐Te Chiu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Hsin‐Hung Chou, Shih‐Yin Lin, Chun-Yi Lin, Wei‐Chen Wu, Jing-Jia Liou, Fangchu Chen, Jen‐Ming Wu, Chao-Tsung Huang, Yikang Shen and Yarsun Hsu. Their work appears in journals such as IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Journal of Systems Architecture, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Multimedia.

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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