Pao‐Chi Chang
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering top 10%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Co-authors
- Robert M. GrayShih-Wei SunChun-Shien LuB.-H. JuangKai-Wen LiangSsu‐Han ChenJia‐Ching WangR. Wang
- Topics
- Video Coding and Compression Technologies (40 papers)Advanced Data Compression Techniques (29 papers)Advanced Vision and Imaging (24 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Pao‐Chi Chang
111 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 553
- Electrical and Electronic Engineering 408
- Signal Processing 384
- Computer Networks and Communications 368
- Artificial Intelligence 178
Countries citing papers authored by Pao‐Chi Chang
This map shows the geographic impact of Pao‐Chi 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 Pao‐Chi Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pao‐Chi Chang more than expected).
Fields of papers citing papers by Pao‐Chi Chang
This network shows the impact of papers produced by Pao‐Chi 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 Pao‐Chi Chang. The network helps show where Pao‐Chi Chang may publish in the future.
Co-authorship network of co-authors of Pao‐Chi Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Pao‐Chi Chang. A scholar is included among the top collaborators of Pao‐Chi 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 Pao‐Chi Chang. Pao‐Chi 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 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 7 | |
| 5 | Acoustic Echo Cancellation Based on Recurrent Neural Network | 1 |
| 6 | 7 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 14 | |
| 10 | 16 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 6 | |
| 16 | 1 | |
| 17 | An Efficient Data Embedding Algorithm for H.263 Compatible Video Coding | 1 |
| 18 | 1 | |
| 19 | 32 | |
| 20 | Hierarchical vector quantizers with table-lookup encoders | 13 |
About Pao‐Chi Chang
Pao‐Chi Chang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Music, having authored 121 papers that have together received 1.2k indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (40 papers), Advanced Data Compression Techniques (29 papers) and Advanced Vision and Imaging (24 papers). The work is most often cited by research in Signal Processing (384 citations), Computer Vision and Pattern Recognition (553 citations) and Computer Networks and Communications (368 citations). Pao‐Chi Chang has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Robert M. Gray, Shih-Wei Sun, Chun-Shien Lu, B.-H. Juang, Kai-Wen Liang, Ssu‐Han Chen, Jia‐Ching Wang, R. Wang, Chih–Wei Huang and Chien-Yao Wang. Their work appears in journals such as Sensors, IEEE Transactions on Vehicular Technology and IEEE Transactions on Cybernetics.
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.