Noise characteristics and prior expectations in human visual speed perception
- Journal
- Nature Neuroscience
In The Last Decade
doi.org/10.1038/nn1669 →Countries where authors are citing Noise characteristics and prior expectations in human visual speed perception
This map shows the geographic impact of Noise characteristics and prior expectations in human visual speed perception. 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 Noise characteristics and prior expectations in human visual speed perception with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noise characteristics and prior expectations in human visual speed perception more than expected).
Fields of papers citing Noise characteristics and prior expectations in human visual speed perception
This network shows the impact of Noise characteristics and prior expectations in human visual speed perception. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Noise characteristics and prior expectations in human visual speed perception.
About Noise characteristics and prior expectations in human visual speed perception
This paper, published in 2006, received 521 indexed citations . Written by Alan A. Stocker and Eero P. Simoncelli covering the research area of Cognitive Neuroscience and Experimental and Cognitive Psychology. It is primarily cited by scholars working on Cognitive Neuroscience (438 citations), Experimental and Cognitive Psychology (107 citations), Computer Vision and Pattern Recognition (93 citations), Social Psychology (66 citations) and Cellular and Molecular Neuroscience (40 citations). Published in Nature Neuroscience.
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.
This paper is also available at doi.org/10.1038/nn1669.