Kao-Hua Chang

972 total citations
12 papers, 632 citations indexed

About

Kao-Hua Chang is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Kao-Hua Chang has authored 12 papers receiving a total of 632 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Mechanical Engineering and 3 papers in Mechanics of Materials. Recurrent topics in Kao-Hua Chang's work include Structural Integrity and Reliability Analysis (6 papers), Face and Expression Recognition (5 papers) and Face recognition and analysis (4 papers). Kao-Hua Chang is often cited by papers focused on Structural Integrity and Reliability Analysis (6 papers), Face and Expression Recognition (5 papers) and Face recognition and analysis (4 papers). Kao-Hua Chang collaborates with scholars based in United States and Taiwan. Kao-Hua Chang's co-authors include Kevin W. Bowyer, Patrick J. Flynn, Min Chul Shin, L.V. Tsap and Xin Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and International Journal of Solids and Structures.

In The Last Decade

Kao-Hua Chang

12 papers receiving 579 citations

Peers

Kao-Hua Chang
Comparison fields: 5 of 72
  • Computer Vision and Pattern Recognition 490
  • Signal Processing 208
  • Mechanical Engineering 67
  • Mechanics of Materials 47
  • Information Systems 42
Replace Tongbo Chen with:
Tongbo Chen Germany
Homayoon Beigi United States
Hiroyasu Koshimizu Japan
Xin Shu China
S. Mann Canada
Rohit Pandey India
Luís Nero Alves Portugal
Liwen Hu United States
Yoshihiro Kanamori Japan
Tongbo Chen Germany View profile →
Citations per field, relative to Kao-Hua Chang
Kao-Hua Chang · 1×
Citations per year, relative to Kao-Hua Chang
Kao-Hua Chang · 1×

Countries citing papers authored by Kao-Hua Chang

Since Specialization
Citations

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

Fields of papers citing papers by Kao-Hua Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kao-Hua Chang. 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 Kao-Hua Chang. The network helps show where Kao-Hua Chang may publish in the future.

Co-authorship network of co-authors of Kao-Hua Chang

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

All Works

12 of 12 papers shown
# Work Indexed citations
1 1
2 1
3 4
4 42
5 21
6 27
7 9
8 279
9 20
10 70
11 111
12 47

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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