Daniel Fišer
Impact in
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- Robotic Path Planning Algorithms
- Aerospace Engineering top 10%
- Robotics and Sensor-Based Localization
- UAV Applications and Optimization
Papers in
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- AI-based Problem Solving and Planning 21
- Logic, Reasoning, and Knowledge 15
- Semantic Web and Ontologies 7
- Machine Learning and Algorithms 5
- Logic, programming, and type systems 3
- Software 5
- Model-Driven Software Engineering Techniques 5
- Co-authors
- Jan Faigl (2 shared papers)Vojtěch Vonásek (3 shared papers)Tomáš Krajník (2 shared papers)Antonín Komenda (8 shared papers)Miroslav Kulich (2 shared papers)Álvaro Torralba (7 shared papers)Jörg Hoffmann (8 shared papers)Wolfgang Faber (2 shared papers)
In The Last Decade
Daniel Fišer
24 papers receiving 354 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 143
- Aerospace Engineering 141
- Artificial Intelligence 138
- Control and Systems Engineering 76
- Computer Networks and Communications 76
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 24 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 225 | |
| 2 | 2012 | 27 | |
| 3 | 2020 | 18 | |
| 4 | 2021 | 14 | |
| 5 | 2018 | 11 | |
| 6 | 2020 | 9 | |
| 7 | 2015 | 9 | |
| 8 | 2019 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2020 | 7 | |
| 11 | 2016 | 6 | |
| 12 | 2014 | 3 | |
| 13 | 2021 | 3 | |
| 14 | 2012 | 2 | |
| 15 | 2022 | 2 | |
| 16 | 2024 | 2 | |
| 17 | Determining Action Reversibility in STRIPS Using Answer Set Programming. | 2020 | 1 |
| 18 | 2021 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2019 | 1 |
About Daniel Fišer
Daniel Fišer is a scholar working on Artificial Intelligence, Software, Computer Vision and Pattern Recognition, Computer Networks and Communications and Industrial and Manufacturing Engineering, having authored 31 papers that have together received 361 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (21 papers), Logic, Reasoning, and Knowledge (15 papers), Semantic Web and Ontologies (7 papers), Model-Driven Software Engineering Techniques (5 papers), Constraint Satisfaction and Optimization (5 papers), Machine Learning and Algorithms (5 papers), Robotic Path Planning Algorithms (4 papers) and Logic, programming, and type systems (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (143 citations), Aerospace Engineering (141 citations), Artificial Intelligence (138 citations), Control and Systems Engineering (76 citations) and Computer Networks and Communications (76 citations). Daniel Fišer has collaborated with scholars based in Czechia, Germany and Denmark. Frequent co-authors include Jan Faigl, Vojtěch Vonásek, Tomáš Krajník, Antonín Komenda, Miroslav Kulich, Álvaro Torralba, Jörg Hoffmann, Wolfgang Faber, Michael Morak and Daniel Höller. Their work appears in journals such as Artificial Intelligence, AI Magazine, Neurocomputing, Journal of Artificial Intelligence Research and Lecture notes in computer science.
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.