Benjamin de Haas
- Cognitive Neuroscience top 2%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Experimental and Cognitive Psychology top 5%
- Social Psychology top 10%
- Co-authors
- D. Samuel SchwarzkopfGeraint ReesBritta KrügerKaren ZentgrafJörn MunzertRudolf StarkKarl R. GegenfurtnerSarah White
- Topics
- Face Recognition and Perception (18 papers)Visual perception and processing mechanisms (18 papers)Visual Attention and Saliency Detection (15 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Benjamin de Haas
63 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 100
- Cognitive Neuroscience 837
- Computer Vision and Pattern Recognition 261
- Radiology, Nuclear Medicine and Imaging 228
- Experimental and Cognitive Psychology 195
- Social Psychology 174
Countries citing papers authored by Benjamin de Haas
This map shows the geographic impact of Benjamin de Haas'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 Benjamin de Haas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin de Haas more than expected).
Fields of papers citing papers by Benjamin de Haas
This network shows the impact of papers produced by Benjamin de Haas. 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 Benjamin de Haas. The network helps show where Benjamin de Haas may publish in the future.
Co-authorship network of co-authors of Benjamin de Haas
This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin de Haas. A scholar is included among the top collaborators of Benjamin de Haas 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 Benjamin de Haas. Benjamin de Haas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 5 | |
| 4 | 7 | |
| 5 | 10 | |
| 6 | 7 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 18 | |
| 11 | 2 | |
| 12 | 9 | |
| 13 | 25 | |
| 14 | 14 | |
| 15 | 49 | |
| 16 | 66 | |
| 17 | 91 | |
| 18 | 86 | |
| 19 | 7 | |
| 20 | 77 |
About Benjamin de Haas
Benjamin de Haas is a scholar working on Sensory Systems, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 68 papers that have together received 1.3k indexed citations. Recurring topics across this work include Face Recognition and Perception (18 papers), Visual perception and processing mechanisms (18 papers) and Visual Attention and Saliency Detection (15 papers). The work is most often cited by research in Cognitive Neuroscience (837 citations), Sensory Systems (128 citations) and Experimental and Cognitive Psychology (195 citations). Benjamin de Haas has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include D. Samuel Schwarzkopf, Geraint Rees, Britta Krüger, Karen Zentgraf, Jörn Munzert, Rudolf Stark, Karl R. Gegenfurtner, Sarah White, Elaine J. Anderson and Iván Alvarez. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.
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.