Ju-Hong Lee
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Computational Mechanics top 10%
- Co-authors
- Deok‐Hwan KimChin‐Wan ChungSun ParkSeok-Ju ChunDaeho KimSeok‐Lyong LeeYen‐Lin ChenJ. Woods
- Topics
- Direction-of-Arrival Estimation Techniques (13 papers)Digital Filter Design and Implementation (10 papers)Speech and Audio Processing (9 papers)
- Journals
- IEEE Transactions on Signal ProcessingIEEE AccessIEEE Transactions on Antennas and Propagation
- Partner nations
- South KoreaTaiwanUnited States
In The Last Decade
Ju-Hong Lee
49 papers receiving 772 citations
Peers
Comparison fields: 5 of 89
- Signal Processing 423
- Artificial Intelligence 301
- Computer Vision and Pattern Recognition 192
- Computer Networks and Communications 173
- Computational Mechanics 105
Countries citing papers authored by Ju-Hong Lee
This map shows the geographic impact of Ju-Hong Lee'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 Ju-Hong Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju-Hong Lee more than expected).
Fields of papers citing papers by Ju-Hong Lee
This network shows the impact of papers produced by Ju-Hong Lee. 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 Ju-Hong Lee. The network helps show where Ju-Hong Lee may publish in the future.
Co-authorship network of co-authors of Ju-Hong Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Ju-Hong Lee. A scholar is included among the top collaborators of Ju-Hong Lee 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 Ju-Hong Lee. Ju-Hong Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 14 | |
| 6 | 2 | |
| 7 | 33 | |
| 8 | 22 | |
| 9 | 24 | |
| 10 | 2 | |
| 11 | Topic-based Multi-document Summarization Using Non-negative Matrix Factorization and K-means | 12 |
| 12 | 57 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 103 | |
| 16 | Minimax Design of Two-Dimensional FIR Linear-Phase Quincunx Filter Banks Satisfying Perfect Reconstruction | 1 |
| 17 | 10 | |
| 18 | 36 | |
| 19 | A Horizontal Partition of the Object-Oriented Database for Efficient Clustering | 0 |
| 20 | 31 |
About Ju-Hong Lee
Ju-Hong Lee is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 53 papers that have together received 843 indexed citations. Recurring topics across this work include Direction-of-Arrival Estimation Techniques (13 papers), Digital Filter Design and Implementation (10 papers) and Speech and Audio Processing (9 papers). The work is most often cited by research in Signal Processing (423 citations), Computer Vision and Pattern Recognition (192 citations) and Artificial Intelligence (301 citations). Ju-Hong Lee has collaborated with scholars based in South Korea, Taiwan and United States. Frequent co-authors include Deok‐Hwan Kim, Chin‐Wan Chung, Sun Park, Seok-Ju Chun, Daeho Kim, Seok‐Lyong Lee, Yen‐Lin Chen, J. Woods, Dong‐Hwan Lee and Chia-Cheng Huang. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Access and IEEE Transactions on Antennas and Propagation.
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.