K. Torkkola
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 10%
- Analytical Chemistry top 5%
- Co-authors
- Jari KangasTeuvo KohonenJorma LaaksonenJohanna HynninenJosé C. Prı́ncipeKenneth E. HildDeniz ErdoğmuşParis Smaragdis
- Topics
- Neural Networks and Applications (14 papers)Speech Recognition and Synthesis (10 papers)Speech and Audio Processing (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Intelligent SystemsPattern Analysis and Applications
- Partner nations
- United StatesFinlandSwitzerland
In The Last Decade
K. Torkkola
28 papers receiving 913 citations
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 504
- Signal Processing 405
- Computer Vision and Pattern Recognition 298
- Computational Mechanics 138
- Analytical Chemistry 110
Countries citing papers authored by K. Torkkola
This map shows the geographic impact of K. Torkkola'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 K. Torkkola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Torkkola more than expected).
Fields of papers citing papers by K. Torkkola
This network shows the impact of papers produced by K. Torkkola. 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 K. Torkkola. The network helps show where K. Torkkola may publish in the future.
Co-authorship network of co-authors of K. Torkkola
This figure shows the co-authorship network connecting the top 25 collaborators of K. Torkkola. A scholar is included among the top collaborators of K. Torkkola 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 K. Torkkola. K. Torkkola is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 105 | |
| 2 | 2 | |
| 3 | 14 | |
| 4 | 12 | |
| 5 | 45 | |
| 6 | 154 | |
| 7 | 1 | |
| 8 | 42 | |
| 9 | 2 | |
| 10 | 15 | |
| 11 | 57 | |
| 12 | 134 | |
| 13 | 0 | |
| 14 | 8 | |
| 15 | 11 | |
| 16 | LVQ_PAK: The Learning Vector Quantization Program Package | 155 |
| 17 | Experiments on the Use of LVQ in Phoneme-Level Segmentation of Speech | 1 |
| 18 | 30 | |
| 19 | 10 | |
| 20 | 26 |
About K. Torkkola
K. Torkkola is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (14 papers), Speech Recognition and Synthesis (10 papers) and Speech and Audio Processing (8 papers). The work is most often cited by research in Signal Processing (405 citations), Artificial Intelligence (504 citations) and Computer Vision and Pattern Recognition (298 citations). K. Torkkola has collaborated with scholars based in United States, Finland and Switzerland. Frequent co-authors include Jari Kangas, Teuvo Kohonen, Jorma Laaksonen, Johanna Hynninen, José C. Prı́ncipe, Kenneth E. Hild, Deniz Erdoğmuş, Paris Smaragdis, Noel Massey and Eugene Tuv. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Intelligent Systems and Pattern Analysis and Applications.
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.