Shi-Kuo Chang
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Information Systems top 10%
- Co-authors
- Qingyun ShiJyh-Sheng KeY.H. ChinArie HasmanVincenzo DeufemiaW. W. ChanGiuseppe PoleseGenoveffa Tortora
- Topics
- Advanced Database Systems and Queries (8 papers)Semantic Web and Ontologies (8 papers)Data Management and Algorithms (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceProceedings of the IEEEIEEE Transactions on Software Engineering
- Partner nations
- United StatesJapanItaly
In The Last Decade
Shi-Kuo Chang
33 papers receiving 753 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 467
- Signal Processing 343
- Computer Networks and Communications 240
- Artificial Intelligence 211
- Information Systems 82
Countries citing papers authored by Shi-Kuo Chang
This map shows the geographic impact of Shi-Kuo 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 Shi-Kuo Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shi-Kuo Chang more than expected).
Fields of papers citing papers by Shi-Kuo Chang
This network shows the impact of papers produced by Shi-Kuo 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 Shi-Kuo Chang. The network helps show where Shi-Kuo Chang may publish in the future.
Co-authorship network of co-authors of Shi-Kuo Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Shi-Kuo Chang. A scholar is included among the top collaborators of Shi-Kuo 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 Shi-Kuo Chang. Shi-Kuo Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | A Multimedia Data Streams Model for Content-based Information Retrieval. | 2 |
| 3 | 22 | |
| 4 | Face Alive Icons. | 1 |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | The Sentient Map and Its Application to the Macro-University E-Learning | 1 |
| 10 | 1 | |
| 11 | 12 | |
| 12 | 5 | |
| 13 | 12 | |
| 14 | Physical Design for Network Databases | 1 |
| 15 | 412 | |
| 16 | Imprecise Database, Imprecise Queries and View Navigation. | 1 |
| 17 | 33 | |
| 18 | 2 | |
| 19 | 13 | |
| 20 | 40 |
About Shi-Kuo Chang
Shi-Kuo Chang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 33 papers that have together received 834 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (8 papers), Semantic Web and Ontologies (8 papers) and Data Management and Algorithms (8 papers). The work is most often cited by research in Signal Processing (343 citations), Computer Vision and Pattern Recognition (467 citations) and Software (40 citations). Shi-Kuo Chang has collaborated with scholars based in United States, Japan and Italy. Frequent co-authors include Qingyun Shi, Jyh-Sheng Ke, Y.H. Chin, Arie Hasman, Vincenzo Deufemia, W. W. Chan, Giuseppe Polese, Genoveffa Tortora, Taieb Znati and Sujata Banerjee. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and IEEE Transactions on Software Engineering.
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.