Michal Hradiš
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Human-Computer Interaction top 5%
- Cognitive Neuroscience
- Artificial Intelligence
- Co-authors
- Pavel ZemčíkRoman BednarikJan KoteraFilip ŠroubekHana VrzákováPavel SvobodaShahram EivaziAdam Herout
- Topics
- Advanced Image and Video Retrieval Techniques (7 papers)Video Analysis and Summarization (5 papers)Image Retrieval and Classification Techniques (5 papers)
In The Last Decade
Michal Hradiš
24 papers receiving 404 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 320
- Media Technology 123
- Human-Computer Interaction 102
- Cognitive Neuroscience 56
- Artificial Intelligence 40
Countries citing papers authored by Michal Hradiš
This map shows the geographic impact of Michal Hradiš'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 Michal Hradiš with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michal Hradiš more than expected).
Fields of papers citing papers by Michal Hradiš
This network shows the impact of papers produced by Michal Hradiš. 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 Michal Hradiš. The network helps show where Michal Hradiš may publish in the future.
Co-authorship network of co-authors of Michal Hradiš
This figure shows the co-authorship network connecting the top 25 collaborators of Michal Hradiš. A scholar is included among the top collaborators of Michal Hradiš 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 Michal Hradiš. Michal Hradiš is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | 6 | |
| 4 | Compression Artifacts Removal Using Convolutional Neural Networks | 23 |
| 5 | 37 | |
| 6 | 6 | |
| 7 | 145 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | 28 | |
| 11 | 5 | |
| 12 | 16 | |
| 13 | 6 | |
| 14 | Brno University of Technology at TRECVid 2010 SIN, CCD | 2 |
| 15 | Brno University of Technology at TRECVid 2008 | 1 |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | 2 | |
| 20 | Real-time Tracking of Participants in Meeting Video | 1 |
About Michal Hradiš
Michal Hradiš is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Media Technology, having authored 25 papers that have together received 429 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (7 papers), Video Analysis and Summarization (5 papers) and Image Retrieval and Classification Techniques (5 papers). The work is most often cited by research in Human-Computer Interaction (102 citations), Computer Vision and Pattern Recognition (320 citations) and Media Technology (123 citations). Michal Hradiš has collaborated with scholars based in Czechia and Finland. Frequent co-authors include Pavel Zemčík, Roman Bednarik, Jan Kotera, Filip Šroubek, Hana Vrzáková, Pavel Svoboda, Shahram Eivazi, Adam Herout, Roman Juránek and Oldřich Kodym. Their work appears in journals such as Pattern Analysis and Applications, International Journal on Document Analysis and Recognition (IJDAR) and Journal of Real-Time Image Processing.
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.