Johan Björck
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
Papers in
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- Machine Learning in Materials Science 3
- Electronic and Structural Properties of Oxides 2
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- Catalysis and Oxidation Reactions 3
- Co-authors
- Furu Wei (1 shared paper)Dong Li (1 shared paper)Zhiliang Peng (1 shared paper)Hangbo Bao (1 shared paper)Wenhui Wang (1 shared paper)Kriti Aggarwal (1 shared paper)Qiang Liu (1 shared paper)Subhojit Som (1 shared paper)
- Journals
- AI Magazine (1 paper)MRS Communications (1 paper)ACS Combinatorial Science (1 paper)Applied Physics Letters (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (5 papers)
- Partner nations
- United StatesChinaSweden
In The Last Decade
Johan Björck
11 papers receiving 410 citations
Johan Björck's Hit Papers
Peers
Comparison fields: 5 of 92
- Computer Vision and Pattern Recognition 195
- Artificial Intelligence 162
- Media Technology 19
- Materials Chemistry 92
- Computational Mathematics 1
Countries citing papers authored by Johan Björck
This map shows the geographic impact of Johan Björck'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 Johan Björck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan Björck more than expected).
Fields of papers citing papers by Johan Björck
This network shows the impact of papers produced by Johan Björck. 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 Johan Björck. The network helps show where Johan Björck may publish in the future.
Co-authors
The 25 scholars most cited alongside Johan Björck, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks Hit paper breakdown → | 2023 | 247 |
| 2 | 2016 | 61 | |
| 3 | 2017 | 34 | |
| 4 | 2019 | 26 | |
| 5 | 2018 | 16 | |
| 6 | 2021 | 15 | |
| 7 | 2021 | 7 | |
| 8 | 2017 | 5 | |
| 9 | Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision | 2021 | 4 |
| 10 | 2018 | 3 | |
| 11 | 2021 | 1 |
About Johan Björck
Johan Björck is a scholar working on Materials Chemistry, Catalysis, Computer Vision and Pattern Recognition, Ecology and Artificial Intelligence, having authored 11 papers that have together received 419 indexed citations. Recurring topics across this work include Catalysis and Oxidation Reactions (3 papers), Machine Learning in Materials Science (3 papers), Electronic and Structural Properties of Oxides (2 papers), Acoustic Wave Resonator Technologies (1 paper), Electron and X-Ray Spectroscopy Techniques (1 paper), Species Distribution and Climate Change (1 paper), Evolutionary Algorithms and Applications (1 paper) and Transition Metal Oxide Nanomaterials (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (195 citations), Artificial Intelligence (162 citations), Media Technology (19 citations), Materials Chemistry (92 citations) and Computational Mathematics (1 citation). Johan Björck has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Furu Wei, Dong Li, Zhiliang Peng, Hangbo Bao, Wenhui Wang, Kriti Aggarwal, Qiang Liu, Subhojit Som, Saksham Singhal and Carla P. Gomes. Their work appears in journals such as AI Magazine, MRS Communications, ACS Combinatorial Science, Applied Physics Letters and Proceedings of the AAAI Conference on Artificial Intelligence.
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.