Ho Bae
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Adversarial Robustness in Machine Learning 4
- Anomaly Detection Techniques and Applications 3
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- Advanced Steganography and Watermarking Techniques 3
- Chaos-based Image/Signal Encryption 2
- Digital Media Forensic Detection 2
- Co-authors
- Sungroh Yoon (11 shared papers)Sunyoung Kwon (2 shared papers)Hyun-Soo Choi (4 shared papers)Seonwoo Min (2 shared papers)Chang‐Ho Yun (1 shared paper)Yo-Han Kim (1 shared paper)Yunheung Paek (3 shared papers)Siwon Kim (1 shared paper)
- Journals
- IEEE Access (3 papers)BMC Bioinformatics (1 paper)Sensors (1 paper)IEEE Transactions on Emerging Topics in Computational Intelligence (1 paper)IEEE Transactions on Dependable and Secure Computing (1 paper)
- Partner nations
- South KoreaPuerto Rico
In The Last Decade
Ho Bae
12 papers receiving 256 citations
Peers
Comparison fields: 5 of 96
- Computational Theory and Mathematics 111
- Health Informatics 5
- Artificial Intelligence 64
- Signal Processing 20
- Chemical Health and Safety 1
Countries citing papers authored by Ho Bae
This map shows the geographic impact of Ho Bae'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 Ho Bae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ho Bae more than expected).
Fields of papers citing papers by Ho Bae
This network shows the impact of papers produced by Ho Bae. 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 Ho Bae. The network helps show where Ho Bae may publish in the future.
Co-authors
The 14 scholars most cited alongside Ho Bae, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 156 | |
| 2 | 2020 | 20 | |
| 3 | 2019 | 18 | |
| 4 | 2019 | 16 | |
| 5 | 2021 | 15 | |
| 6 | 2021 | 11 | |
| 7 | 2020 | 11 | |
| 8 | 2018 | 5 | |
| 9 | 2018 | 5 | |
| 10 | 2020 | 4 | |
| 11 | 2024 | 3 | |
| 12 | 2022 | 2 | |
| 13 | 2023 | 0 | |
| 14 | 2023 | 0 |
About Ho Bae
Ho Bae is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications and Molecular Biology, having authored 14 papers that have together received 266 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Advanced Malware Detection Techniques (3 papers), Advanced Steganography and Watermarking Techniques (3 papers), Anomaly Detection Techniques and Applications (3 papers), Chaos-based Image/Signal Encryption (2 papers), Digital Media Forensic Detection (2 papers), Gaze Tracking and Assistive Technology (1 paper) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Computational Theory and Mathematics (111 citations), Health Informatics (5 citations), Artificial Intelligence (64 citations), Signal Processing (20 citations) and Chemical Health and Safety (1 citation). Ho Bae has collaborated with scholars based in South Korea and Puerto Rico. Frequent co-authors include Sungroh Yoon, Sunyoung Kwon, Hyun-Soo Choi, Seonwoo Min, Chang‐Ho Yun, Yo-Han Kim, Yunheung Paek, Siwon Kim, Uiwon Hwang and Byunghan Lee. Their work appears in journals such as IEEE Access, BMC Bioinformatics, Sensors, IEEE Transactions on Emerging Topics in Computational Intelligence and IEEE Transactions on Dependable and Secure Computing.
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.