James Jin Kang
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Oncology
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Co-authors
- Muhammad Fazal IjazAkash Kumar BhoiParvathaneni Naga SrinivasuWonjoon KimSaifur RahmanJingwen ZhouSasan AdibiPatryk Szewczyk
- Topics
- Wireless Body Area Networks (13 papers)IoT and Edge/Fog Computing (12 papers)Context-Aware Activity Recognition Systems (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSensors
In The Last Decade
James Jin Kang
36 papers receiving 981 citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 315
- Computer Networks and Communications 235
- Oncology 201
- Computer Vision and Pattern Recognition 186
- Biomedical Engineering 151
Countries citing papers authored by James Jin Kang
This map shows the geographic impact of James Jin 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 James Jin Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Jin Kang more than expected).
Fields of papers citing papers by James Jin Kang
This network shows the impact of papers produced by James Jin 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 James Jin Kang. The network helps show where James Jin Kang may publish in the future.
Co-authorship network of co-authors of James Jin Kang
This figure shows the co-authorship network connecting the top 25 collaborators of James Jin Kang. A scholar is included among the top collaborators of James Jin Kang 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 James Jin Kang. James Jin Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challengesbreakdown → | 142 |
| 3 | 35 | |
| 4 | Classification of Skin Disease Using Deep Learning Neural Networks with MobileNet V2 and LSTMbreakdown → | 495 |
| 5 | 10 | |
| 6 | 8 | |
| 7 | 6 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | INTELLIGENT PERSONAL HEALTH DEVICES CONVERGED WITH INTERNET OF THINGS NETWORKS | 9 |
| 13 | An inference system framework for personal sensor devices in mobile health and internet of things networks | 16 |
| 14 | 14 | |
| 15 | 2 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | 12 | |
| 19 | 12 | |
| 20 | 31 |
About James Jin Kang
James Jin Kang is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Bioengineering, having authored 37 papers that have together received 1.0k indexed citations. Recurring topics across this work include Wireless Body Area Networks (13 papers), IoT and Edge/Fog Computing (12 papers) and Context-Aware Activity Recognition Systems (10 papers). The work is most often cited by research in Health Informatics (25 citations), Computer Networks and Communications (235 citations) and Signal Processing (109 citations). James Jin Kang has collaborated with scholars based in Australia, Iran and Taiwan. Frequent co-authors include Muhammad Fazal Ijaz, Akash Kumar Bhoi, Parvathaneni Naga Srinivasu, Wonjoon Kim, Saifur Rahman, Jingwen Zhou, Sasan Adibi, Patryk Szewczyk, Wencheng Yang and Paul Haskell‐Dowland. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access 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.