Sizhen Bian
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Computer Networks and Communications
- Human-Computer Interaction top 10%
- Co-authors
- Paul LukowiczBo ZhouVítor Fortes ReyMichele MagnoOliver AmftGernot BahleSungho SuhYawei Li
- Topics
- Context-Aware Activity Recognition Systems (13 papers)Indoor and Outdoor Localization Technologies (8 papers)Gaze Tracking and Assistive Technology (4 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- GermanySwitzerlandCanada
In The Last Decade
Sizhen Bian
27 papers receiving 290 citations
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 120
- Electrical and Electronic Engineering 102
- Biomedical Engineering 83
- Computer Networks and Communications 50
- Human-Computer Interaction 50
Countries citing papers authored by Sizhen Bian
This map shows the geographic impact of Sizhen Bian'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 Sizhen Bian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sizhen Bian more than expected).
Fields of papers citing papers by Sizhen Bian
This network shows the impact of papers produced by Sizhen Bian. 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 Sizhen Bian. The network helps show where Sizhen Bian may publish in the future.
Co-authorship network of co-authors of Sizhen Bian
This figure shows the co-authorship network connecting the top 25 collaborators of Sizhen Bian. A scholar is included among the top collaborators of Sizhen Bian 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 Sizhen Bian. Sizhen Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 8 | |
| 15 | 3 | |
| 16 | 28 | |
| 17 | 14 | |
| 18 | 5 | |
| 19 | 25 | |
| 20 | 2 |
About Sizhen Bian
Sizhen Bian is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 33 papers that have together received 305 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (13 papers), Indoor and Outdoor Localization Technologies (8 papers) and Gaze Tracking and Assistive Technology (4 papers). The work is most often cited by research in Human-Computer Interaction (50 citations), Computer Vision and Pattern Recognition (120 citations) and Computer Networks and Communications (50 citations). Sizhen Bian has collaborated with scholars based in Germany, Switzerland and Canada. Frequent co-authors include Paul Lukowicz, Bo Zhou, Vítor Fortes Rey, Michele Magno, Oliver Amft, Gernot Bahle, Sungho Suh, Yawei Li, Jože M. Rožanec and Alfio Di Mauro. Their work appears in journals such as Scientific Reports, Sensors and IEEE Internet of Things Journal.
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.