Yooju Shin
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Industrial and Manufacturing Engineering top 10%
- Signal Processing
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Jae-Gil LeeHwanjun SongMinseok KimByung Suk LeeKijung ShinJae Hyun ParkDoyoung KimByung Ho Lee
- Topics
- Time Series Analysis and Forecasting (3 papers)Anomaly Detection Techniques and Applications (3 papers)Data Stream Mining Techniques (2 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Yooju Shin
6 papers receiving 593 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 382
- Computer Vision and Pattern Recognition 162
- Industrial and Manufacturing Engineering 46
- Signal Processing 43
- Radiology, Nuclear Medicine and Imaging 36
Countries citing papers authored by Yooju Shin
This map shows the geographic impact of Yooju Shin'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 Yooju Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yooju Shin more than expected).
Fields of papers citing papers by Yooju Shin
This network shows the impact of papers produced by Yooju Shin. 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 Yooju Shin. The network helps show where Yooju Shin may publish in the future.
Co-authorship network of co-authors of Yooju Shin
This figure shows the co-authorship network connecting the top 25 collaborators of Yooju Shin. A scholar is included among the top collaborators of Yooju Shin 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 Yooju Shin. Yooju Shin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 12 | |
| 6 | 9 | |
| 7 | Learning From Noisy Labels With Deep Neural Networks: A Surveybreakdown → | 568 |
| 8 | 12 | |
| 9 | 3 |
About Yooju Shin
Yooju Shin is a scholar working on Signal Processing, Artificial Intelligence and Computer Science Applications, having authored 9 papers that have together received 605 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (382 citations), Computer Vision and Pattern Recognition (162 citations) and Health Informatics (7 citations). Yooju Shin has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Jae-Gil Lee, Hwanjun Song, Minseok Kim, Byung Suk Lee, Kijung Shin, Jae Hyun Park, Doyoung Kim and Byung Ho Lee. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems and Proceedings of the AAAI Conference on Artificial Intelligence.
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.