Sung-Yang Bang
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Signal Processing
- Molecular Biology
- Media Technology
- Co-authors
- Seungjin ChoiZoubin GhahramaniJong KimDaijin KimGajendra P. S. RaghavaDae-Hwan KimT. J. KimHeyjin Kim
- Topics
- Handwritten Text Recognition Techniques (5 papers)Neural Networks and Applications (3 papers)RNA and protein synthesis mechanisms (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionPattern Recognition Letters
- Partner nations
- South KoreaIndiaSouth Sudan
In The Last Decade
Sung-Yang Bang
19 papers receiving 170 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 85
- Artificial Intelligence 66
- Signal Processing 33
- Molecular Biology 27
- Media Technology 20
Countries citing papers authored by Sung-Yang Bang
This map shows the geographic impact of Sung-Yang Bang'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 Sung-Yang Bang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sung-Yang Bang more than expected).
Fields of papers citing papers by Sung-Yang Bang
This network shows the impact of papers produced by Sung-Yang Bang. 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 Sung-Yang Bang. The network helps show where Sung-Yang Bang may publish in the future.
Co-authorship network of co-authors of Sung-Yang Bang
This figure shows the co-authorship network connecting the top 25 collaborators of Sung-Yang Bang. A scholar is included among the top collaborators of Sung-Yang Bang 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 Sung-Yang Bang. Sung-Yang Bang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 26 | |
| 2 | Robust Location Tracking Using a Double Layered Particle Filter | 1 |
| 3 | 7 | |
| 4 | 19 | |
| 5 | Face Recognition using LDA Mixture Model | 1 |
| 6 | 28 | |
| 7 | Analysis of Interaction in Multiple Genes Using Independent Subspace Analysis | 1 |
| 8 | 19 | |
| 9 | 6 | |
| 10 | 16 | |
| 11 | 8 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 2 | |
| 15 | 연속 상태 공간을 갖는 조합 최적화 문제를 위한 수정된 평균장 어닐링 알고리즘 | 0 |
| 16 | 9 | |
| 17 | 1 | |
| 18 | 22 | |
| 19 | 1 | |
| 20 | 10 |
About Sung-Yang Bang
Sung-Yang Bang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Transportation, having authored 20 papers that have together received 184 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (5 papers), Neural Networks and Applications (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (85 citations), Signal Processing (33 citations) and Media Technology (20 citations). Sung-Yang Bang has collaborated with scholars based in South Korea, India and South Sudan. Frequent co-authors include Seungjin Choi, Zoubin Ghahramani, Seungjin Choi, Jong Kim, Daijin Kim, Gajendra P. S. Raghava, Dae-Hwan Kim, T. J. Kim, Seungjin Choi and Heyjin Kim. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Pattern Recognition Letters.
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.