Annette M. Schmid
- Cognitive Neuroscience top 2%
- Experimental and Cognitive Psychology top 5%
- Social Psychology top 10%
- Computer Vision and Pattern Recognition top 10%
- Developmental and Educational Psychology top 10%
- Co-authors
- Ksenija MarinkovićEric HalgrenMoshe BarMatti HämäläinenDaniel L. SchacterK. KassamJasmine BoshyanAnders M. Dale
- Topics
- Visual perception and processing mechanisms (4 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Neural dynamics and brain function (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Annette M. Schmid
8 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Cognitive Neuroscience 1.1k
- Experimental and Cognitive Psychology 224
- Social Psychology 136
- Computer Vision and Pattern Recognition 99
- Developmental and Educational Psychology 79
Countries citing papers authored by Annette M. Schmid
This map shows the geographic impact of Annette M. Schmid'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 Annette M. Schmid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annette M. Schmid more than expected).
Fields of papers citing papers by Annette M. Schmid
This network shows the impact of papers produced by Annette M. Schmid. 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 Annette M. Schmid. The network helps show where Annette M. Schmid may publish in the future.
Co-authorship network of co-authors of Annette M. Schmid
This figure shows the co-authorship network connecting the top 25 collaborators of Annette M. Schmid. A scholar is included among the top collaborators of Annette M. Schmid 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 Annette M. Schmid. Annette M. Schmid is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 19 | |
| 3 | 1 | |
| 4 | 65 | |
| 5 | Top-down facilitation of visual recognitionbreakdown → | 1123 |
| 6 | 3 | |
| 7 | 19 | |
| 8 | 40 |
About Annette M. Schmid
Annette M. Schmid is a scholar working on Cognitive Neuroscience, Endocrine and Autonomic Systems and Statistics, Probability and Uncertainty, having authored 8 papers that have together received 1.3k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Experimental and Cognitive Psychology (224 citations) and Sensory Systems (33 citations). Annette M. Schmid has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Ksenija Marinković, Eric Halgren, Moshe Bar, Matti Hämäläinen, Daniel L. Schacter, K. Kassam, Jasmine Boshyan, Anders M. Dale, Avniel Singh Ghuman and Bruce R. Rosen. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Experimental Brain Research.
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.