Kimmo Kärkkäinen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Safety Research top 10%
- Signal Processing
- Cognitive Neuroscience
- Co-authors
- Jungseock JooMajid SarrafzadehMohammad KachueeKristian HartikainenAarne HalmeCory J. CascalheiraChenglin HongIan W. Holloway
- Topics
- Machine Learning and Data Classification (3 papers)Face recognition and analysis (2 papers)Ethics and Social Impacts of AI (1 paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceLGBT HealthJMIR Research Protocols
- Partner nations
- United States
In The Last Decade
Kimmo Kärkkäinen
9 papers receiving 297 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 152
- Artificial Intelligence 133
- Safety Research 41
- Signal Processing 39
- Cognitive Neuroscience 24
Countries citing papers authored by Kimmo Kärkkäinen
This map shows the geographic impact of Kimmo Kärkkäinen'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 Kimmo Kärkkäinen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kimmo Kärkkäinen more than expected).
Fields of papers citing papers by Kimmo Kärkkäinen
This network shows the impact of papers produced by Kimmo Kärkkäinen. 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 Kimmo Kärkkäinen. The network helps show where Kimmo Kärkkäinen may publish in the future.
Co-authorship network of co-authors of Kimmo Kärkkäinen
This figure shows the co-authorship network connecting the top 25 collaborators of Kimmo Kärkkäinen. A scholar is included among the top collaborators of Kimmo Kärkkäinen 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 Kimmo Kärkkäinen. Kimmo Kärkkäinen 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 | 2 | |
| 3 | 4 | |
| 4 | FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigationbreakdown → | 248 |
| 5 | 16 | |
| 6 | 6 | |
| 7 | 17 | |
| 8 | Nutrition and Health Data for Cost-Sensitive Learning. | 4 |
| 9 | Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams | 3 |
| 10 | 11 |
About Kimmo Kärkkäinen
Kimmo Kärkkäinen is a scholar working on Issues, ethics and legal aspects, Health Information Management and Virology, having authored 10 papers that have together received 311 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (3 papers), Face recognition and analysis (2 papers) and Ethics and Social Impacts of AI (1 paper). The work is most often cited by research in Health Informatics (12 citations), Computer Vision and Pattern Recognition (152 citations) and Safety Research (41 citations). Kimmo Kärkkäinen has collaborated with scholars based in United States. Frequent co-authors include Jungseock Joo, Majid Sarrafzadeh, Mohammad Kachuee, Kristian Hartikainen, Aarne Halme, Cory J. Cascalheira, Chenglin Hong, Ian W. Holloway and Jeffrey T. Parsons. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, LGBT Health and JMIR Research Protocols.
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.