Dae-Ki Kang
- Accounting top 5%
- Artificial Intelligence top 2%
- Imbalanced Data Classification Techniques 11
- Domain Adaptation and Few-Shot Learning 8
- Anomaly Detection Techniques and Applications 8
- Text and Document Classification Technologies 7
- Adversarial Robustness in Machine Learning 6
- Machine Learning and Data Classification 6
- Signal Processing top 5%
- Finance top 5%
- Information Systems top 5%
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- Network Security and Intrusion Detection 7
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- Advanced Neural Network Applications 6
- Co-authors
- Imrus SalehinHong Bae KimVasant HonavarAdrian SilvescuAhmed Abdulhakim Al-AbsiPrasant Kumar PattnaikJun ZhangByung-Gook Lee
- Journals
- Applied Intelligence (8 papers)Expert Systems with Applications (6 papers)Applied Sciences (6 papers)
- Partner nations
- South KoreaChinaUnited States
In The Last Decade
Dae-Ki Kang
81 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Accounting 249
- Artificial Intelligence 569
- Signal Processing 136
- Finance 97
- Information Systems 180
Countries citing papers authored by Dae-Ki Kang
This map shows the geographic impact of Dae-Ki 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 Dae-Ki Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dae-Ki Kang more than expected).
Fields of papers citing papers by Dae-Ki Kang
This network shows the impact of papers produced by Dae-Ki 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 Dae-Ki Kang. The network helps show where Dae-Ki Kang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dae-Ki Kang, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 2 | |
| 8 | 2021 | 2 | |
| 9 | 2019 | 0 | |
| 10 | 2019 | 1 | |
| 11 | 2019 | 1 | |
| 12 | 2019 | 2 | |
| 13 | Wine Quality Classification with Multilayer Perceptron | 2018 | 5 |
| 14 | 2018 | 102 | |
| 15 | 2017 | 4 | |
| 16 | 2015 | 6 | |
| 17 | Geometric Mean based Boosting Algorithm to Resolve Data Imbalance Problem | 2013 | 4 |
| 18 | Evaluation of online social network games usability using verbal protocol analysis | 2012 | 2 |
| 19 | Wrapper Induction based on Minimum Description Length using a Suffix Tree | 2007 | 1 |
| 20 | RNBL-MN: A recursive naive Bayes learner for sequence classification | 2006 | 0 |
About Dae-Ki Kang
Dae-Ki Kang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Human-Computer Interaction, Information Systems and Computer Networks and Communications, having authored 91 papers that have together received 1.1k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (11 papers), Domain Adaptation and Few-Shot Learning (8 papers), Anomaly Detection Techniques and Applications (8 papers), Network Security and Intrusion Detection (7 papers), Text and Document Classification Technologies (7 papers), Adversarial Robustness in Machine Learning (6 papers), Advanced Neural Network Applications (6 papers) and Machine Learning and Data Classification (6 papers). The work is most often cited by research in Accounting (249 citations), Artificial Intelligence (569 citations), Signal Processing (136 citations), Finance (97 citations) and Information Systems (180 citations). Dae-Ki Kang has collaborated with scholars based in South Korea, China and United States. Frequent co-authors include Imrus Salehin, Hong Bae Kim, Vasant Honavar, Adrian Silvescu, Ahmed Abdulhakim Al-Absi, Prasant Kumar Pattnaik, Jun Zhang, Byung-Gook Lee, Zhiyong Wang and Rui Fu. Their work appears in journals such as Applied Intelligence, Expert Systems with Applications, Applied Sciences, Electronics and Sensors.
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.