Shao-Kuo Tai

461 citations
14 papers · 323 indexed · h-index 7
Topics
Vehicle License Plate Recognition (4 papers)AI in cancer detection (4 papers)Advanced Neural Network Applications (4 papers)
Partner nations
TaiwanIndonesiaGermany

In The Last Decade

Shao-Kuo Tai

13 papers receiving 309 citations

Peers

Shao-Kuo Tai
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 148
  • Cognitive Neuroscience 66
  • Media Technology 58
  • Artificial Intelligence 52
  • Human-Computer Interaction 51
Replace Tae‐Koo Kang with:
Tae‐Koo Kang South Korea
Haowen Wang China
Mouna Afif Tunisia
A. Belén Moreno Spain
Riadh Ayachi Tunisia
Weijian Hu China
Wei You China
Zhiwen Shao China
Maurizio Ficocelli Canada
Uipil Chong South Korea
Shao-Kuo Tai relative to Tae‐Koo Kang South Korea Tae‐Koo Kang's profile →
Citations per field
00.5×1.5×2.0×
Tae‐Koo Kang · 1×
Citations per year

Countries citing papers authored by Shao-Kuo Tai

Since Specialization
Citations

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

Fields of papers citing papers by Shao-Kuo Tai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao-Kuo Tai. 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 Shao-Kuo Tai. The network helps show where Shao-Kuo Tai may publish in the future.

Co-authorship network of co-authors of Shao-Kuo Tai

This figure shows the co-authorship network connecting the top 25 collaborators of Shao-Kuo Tai. A scholar is included among the top collaborators of Shao-Kuo Tai 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 Shao-Kuo Tai. Shao-Kuo Tai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 1
2 0
3 2
4 78
5 48
6 61
7
Grading Liver Carcinoma Stage Analyzing Cell Biopsy Image
1
8 55
9 2
10 52
11 6
12 3
13
Classification of prostatic biopsy
10
14
Computer-assisted Detection and Grading of Prostatic Cancer in Biopsy Image
4

About Shao-Kuo Tai

Shao-Kuo Tai is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 14 papers that have together received 323 indexed citations. Recurring topics across this work include Vehicle License Plate Recognition (4 papers), AI in cancer detection (4 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Human-Computer Interaction (51 citations), Computer Vision and Pattern Recognition (148 citations) and Media Technology (58 citations). Shao-Kuo Tai has collaborated with scholars based in Taiwan, Indonesia and Germany. Frequent co-authors include Rung-Ching Chen, Christine Dewi, Yanting Liu, Hendry Hendry, Xiaoyi Jiang, Hui Yu, Shu‐Chuan Lin, Yee‐Jee Jan, Chengyi Li and Goutam Chakraborty. Their work appears in journals such as IEEE Access, Applied Sciences and Neural Computing and 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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