Bong-Nam Kang
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Information Systems
- Artificial Intelligence
- Co-authors
- Daijin KimMahmut KandemirM. IrwinR. ChandramouliN. VijaykrishnanGong ChenYong-Joong KimYonghyun Kim
- Topics
- Face recognition and analysis (8 papers)Face and Expression Recognition (7 papers)Advanced Image and Video Retrieval Techniques (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Networks and CommunicationsSignal Processing
- Journals
- IEEE Transactions on Parallel and Distributed SystemsProceedings - International Conference on Pattern Recognition
- Partner nations
- South KoreaUnited States
In The Last Decade
Bong-Nam Kang
15 papers receiving 202 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 131
- Computer Networks and Communications 97
- Electrical and Electronic Engineering 46
- Information Systems 35
- Artificial Intelligence 31
Countries citing papers authored by Bong-Nam Kang
This map shows the geographic impact of Bong-Nam Kang'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 Bong-Nam Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bong-Nam Kang more than expected).
Fields of papers citing papers by Bong-Nam Kang
This network shows the impact of papers produced by Bong-Nam Kang. 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 Bong-Nam Kang. The network helps show where Bong-Nam Kang may publish in the future.
Co-authorship network of co-authors of Bong-Nam Kang
This figure shows the co-authorship network connecting the top 25 collaborators of Bong-Nam Kang. A scholar is included among the top collaborators of Bong-Nam Kang 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 Bong-Nam Kang. Bong-Nam Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 12 | |
| 4 | 5 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 33 | |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 6 | |
| 11 | 6 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | 33 | |
| 15 | 88 |
About Bong-Nam Kang
Bong-Nam Kang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Biophysics, having authored 15 papers that have together received 209 indexed citations. Recurring topics across this work include Face recognition and analysis (8 papers), Face and Expression Recognition (7 papers) and Advanced Image and Video Retrieval Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (131 citations), Computer Networks and Communications (97 citations) and Signal Processing (30 citations). Bong-Nam Kang has collaborated with scholars based in South Korea and United States. Frequent co-authors include Daijin Kim, Mahmut Kandemir, M. Irwin, R. Chandramouli, N. Vijaykrishnan, Gong Chen, Yong-Joong Kim, Yonghyun Kim, Bongjin Jun and Ju Young Lee. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems and Proceedings - International Conference on Pattern Recognition.
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.