Daniel Fišer
Impact in
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- AI-based Problem Solving and Planning
- Logic, Reasoning, and Knowledge
- Semantic Web and Ontologies
- Logic, programming, and type systems
- Machine Learning and Algorithms
- Multi-Agent Systems and Negotiation
Papers in
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- AI-based Problem Solving and Planning 18
- Logic, Reasoning, and Knowledge 14
- Semantic Web and Ontologies 5
- Machine Learning and Algorithms 4
- Logic, programming, and type systems 2
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- Robotic Path Planning Algorithms 3
- Co-authors
- Antonín Komenda (7 shared papers)Miroslav Kulich (2 shared papers)Jan Faigl (1 shared paper)Álvaro Torralba (6 shared papers)Jörg Hoffmann (5 shared papers)Daniel Höller (2 shared papers)Lukáš Chrpa (2 shared papers)Wolfgang Faber (2 shared papers)
- Journals
- Neurocomputing (1 paper)AI Magazine (1 paper)Journal of Artificial Intelligence Research (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (5 papers)International Conference on Lightning Protection (1 paper)
In The Last Decade
Daniel Fišer
19 papers receiving 102 citations
Peers
Comparison fields: 5 of 28
- Software 12
- Artificial Intelligence 86
- Health Informatics 3
- Computer Vision and Pattern Recognition 23
- Computer Graphics and Computer-Aided Design 2
Countries citing papers authored by Daniel Fišer
This map shows the geographic impact of Daniel Fišer'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 Fišer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Fišer more than expected).
Fields of papers citing papers by Daniel Fišer
This network shows the impact of papers produced by Daniel Fišer. 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 Fišer. The network helps show where Daniel Fišer may publish in the future.
Co-authors
The 22 scholars most cited alongside Daniel Fišer, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 22 | |
| 2 | 2020 | 17 | |
| 3 | 2021 | 13 | |
| 4 | 2018 | 8 | |
| 5 | 2015 | 7 | |
| 6 | 2019 | 7 | |
| 7 | 2020 | 6 | |
| 8 | 2016 | 5 | |
| 9 | 2020 | 5 | |
| 10 | 2022 | 3 | |
| 11 | 2021 | 3 | |
| 12 | 2024 | 1 | |
| 13 | 2019 | 1 | |
| 14 | 2019 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2012 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2022 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2023 | 0 |
About Daniel Fišer
Daniel Fišer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Software, Computer Networks and Communications and Signal Processing, having authored 24 papers that have together received 104 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (18 papers), Logic, Reasoning, and Knowledge (14 papers), Semantic Web and Ontologies (5 papers), Machine Learning and Algorithms (4 papers), Model-Driven Software Engineering Techniques (4 papers), Robotic Path Planning Algorithms (3 papers), Constraint Satisfaction and Optimization (3 papers) and Logic, programming, and type systems (2 papers). The work is most often cited by research in Software (12 citations), Artificial Intelligence (86 citations), Health Informatics (3 citations), Computer Vision and Pattern Recognition (23 citations) and Computer Graphics and Computer-Aided Design (2 citations). Daniel Fišer has collaborated with scholars based in Czechia, Germany and Denmark. Frequent co-authors include Antonín Komenda, Miroslav Kulich, Jan Faigl, Álvaro Torralba, Jörg Hoffmann, Daniel Höller, Lukáš Chrpa, Wolfgang Faber, Florian Pommerening and Scott Sanner. Their work appears in journals such as Neurocomputing, AI Magazine, Journal of Artificial Intelligence Research, Proceedings of the AAAI Conference on Artificial Intelligence and International Conference on Lightning Protection.
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.