A. Kosmala
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Human-Computer Interaction top 5%
- Signal Processing
- Media Technology top 10%
- Topics
- Handwritten Text Recognition Techniques (15 papers)Natural Language Processing Techniques (11 papers)Speech Recognition and Synthesis (6 papers)
- Journals
- Data Archiving and Networked Services (DANS)
In The Last Decade
A. Kosmala
20 papers receiving 262 citations
Peers
Comparison fields: 5 of 30
- Computer Vision and Pattern Recognition 274
- Artificial Intelligence 147
- Human-Computer Interaction 78
- Signal Processing 35
- Media Technology 33
Countries citing papers authored by A. Kosmala
This map shows the geographic impact of A. Kosmala'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 A. Kosmala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Kosmala more than expected).
Fields of papers citing papers by A. Kosmala
This network shows the impact of papers produced by A. Kosmala. 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 A. Kosmala. The network helps show where A. Kosmala may publish in the future.
Co-authorship network of co-authors of A. Kosmala
This figure shows the co-authorship network connecting the top 25 collaborators of A. Kosmala. A scholar is included among the top collaborators of A. Kosmala 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 A. Kosmala. A. Kosmala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | HMM BASED HIGH ACCURACY OFF-LINE CURSIVE HANDWRITING RECOGNITION BY A BASELINE DETECTION ERROR TOLERANT FEATURE EXTRACTION APPROACH | 5 |
| 2 | OFF-LINE HANDWRITING RECOGNITION USING VARIOUS HYBRID MODELING TECHNIQUES AND CHARACTER N-GRAMS | 17 |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 73 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 58 | |
| 9 | 5 | |
| 10 | 21 | |
| 11 | 1 | |
| 12 | Audio-Visual Analysis of Multimedia Documents for Automatic Topic Identification | 1 |
| 13 | 9 | |
| 14 | 17 | |
| 15 | 30 | |
| 16 | 7 | |
| 17 | 16 | |
| 18 | 6 | |
| 19 | High Performance Real-Time Gesture Recognition Using Hidden Markov Models | 5 |
| 20 | 21 |
About A. Kosmala
A. Kosmala is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 21 papers that have together received 319 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (15 papers), Natural Language Processing Techniques (11 papers) and Speech Recognition and Synthesis (6 papers). The work is most often cited by research in Human-Computer Interaction (78 citations), Computer Vision and Pattern Recognition (274 citations) and Artificial Intelligence (147 citations). A. Kosmala has collaborated with scholars based in Germany and Russia. Frequent co-authors include Gerhard Rigoll, Stefan Eickeler, Daniel Willett, Mike Schuster, Sebastian Werner and Frank Wallhoff. Their work appears in journals such as Data Archiving and Networked Services (DANS).
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.