Daniel Hládek
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Speech Recognition and Synthesis
- Topic Modeling
- Speech and dialogue systems
- AI in Service Interactions
- Fuzzy Logic and Control Systems
- Computer Science Applications top 10%
- Online Learning and Analytics
Papers in
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- Natural Language Processing Techniques 40
- Speech Recognition and Synthesis 25
- Speech and dialogue systems 20
- Topic Modeling 18
- Cognitive Computing and Networks 4
- Fuzzy Logic and Control Systems 3
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- Robotic Path Planning Algorithms 4
- Co-authors
- Ján Staš (45 shared papers)Matúš Pleva (28 shared papers)Jozef Juhár (39 shared papers)Stanislav Ondáš (11 shared papers)Ján Vaščák (2 shared papers)Peter Sinčák (2 shared papers)László Kovács (3 shared papers)Patrick Bours (2 shared papers)
In The Last Decade
Daniel Hládek
60 papers receiving 384 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 299
- Computer Science Applications 33
- Signal Processing 47
- Health Informatics 4
- Control and Systems Engineering 64
Countries citing papers authored by Daniel Hládek
This map shows the geographic impact of Daniel Hládek'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 Daniel Hládek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Hládek more than expected).
Fields of papers citing papers by Daniel Hládek
This network shows the impact of papers produced by Daniel Hládek. 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 Daniel Hládek. The network helps show where Daniel Hládek may publish in the future.
Co-authors
The 12 scholars most cited alongside Daniel Hládek, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 57 | |
| 2 | 2019 | 54 | |
| 3 | MULTI-ROBOT CONTROL SYSTEM FOR PURSUIT-EVASION PROBLEM | 2009 | 47 |
| 4 | 2008 | 25 | |
| 5 | 2014 | 16 | |
| 6 | 2014 | 15 | |
| 7 | 2016 | 14 | |
| 8 | Dagger: The Slovak morphological classifier | 2012 | 11 |
| 9 | 2014 | 11 | |
| 10 | 2014 | 10 | |
| 11 | 2018 | 10 | |
| 12 | 2016 | 9 | |
| 13 | 2013 | 9 | |
| 14 | 2011 | 7 | |
| 15 | 2023 | 7 | |
| 16 | 2019 | 6 | |
| 17 | TUKE at MediaEval 2013 Spoken Web Search Task. | 2013 | 5 |
| 18 | 2016 | 5 | |
| 19 | 2008 | 5 | |
| 20 | 2014 | 5 |
About Daniel Hládek
Daniel Hládek is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Information Systems and Signal Processing, having authored 66 papers that have together received 417 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (40 papers), Speech Recognition and Synthesis (25 papers), Speech and dialogue systems (20 papers), Topic Modeling (18 papers), Robotics and Automated Systems (7 papers), Cognitive Computing and Networks (4 papers), Robotic Path Planning Algorithms (4 papers) and Fuzzy Logic and Control Systems (3 papers). The work is most often cited by research in Artificial Intelligence (299 citations), Computer Science Applications (33 citations), Signal Processing (47 citations), Health Informatics (4 citations) and Control and Systems Engineering (64 citations). Daniel Hládek has collaborated with scholars based in Slovakia, Taiwan and Hungary. Frequent co-authors include Ján Staš, Matúš Pleva, Jozef Juhár, Stanislav Ondáš, Ján Vaščák, Peter Sinčák, László Kovács, Patrick Bours, Ming-Hsiang Su and Julius Zimmermann. Their work appears in journals such as IEEE Access, Electronics, Language Resources and Evaluation, Lecture notes in computer science and Multimedia Tools 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.