Adam M. Larson

1.4k total citations
44 papers, 946 citations indexed

About

Adam M. Larson is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Adam M. Larson has authored 44 papers receiving a total of 946 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 17 papers in Cognitive Neuroscience and 13 papers in Experimental and Cognitive Psychology. Recurrent topics in Adam M. Larson's work include Visual Attention and Saliency Detection (16 papers), Visual perception and processing mechanisms (13 papers) and Visual and Cognitive Learning Processes (11 papers). Adam M. Larson is often cited by papers focused on Visual Attention and Saliency Detection (16 papers), Visual perception and processing mechanisms (13 papers) and Visual and Cognitive Learning Processes (11 papers). Adam M. Larson collaborates with scholars based in United States, United Kingdom and Germany. Adam M. Larson's co-authors include Lester C. Loschky, Joseph P. Magliano, Tim J. Smith, Alvin T. Yeh, N. Sanjay Rebello, Adrian Madsen, Joseph P. Magliano, Steve Pekarek, Michelle Bash and Peter Saggau and has published in prestigious journals such as PLoS ONE, Nature Photonics and Biological Psychiatry.

In The Last Decade

Adam M. Larson

42 papers receiving 913 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Adam M. Larson United States 15 385 243 224 108 107 44 946
Najib J. Majaj United States 18 2.3k 6.1× 480 2.0× 312 1.4× 231 2.1× 106 1.0× 46 2.7k
Bosco S. Tjan United States 27 2.1k 5.4× 392 1.6× 448 2.0× 223 2.1× 241 2.3× 87 2.5k
Birgitta Dresp France 22 939 2.4× 153 0.6× 133 0.6× 19 0.2× 40 0.4× 88 1.3k
Jukka Saarinen Finland 24 1.0k 2.7× 115 0.5× 285 1.3× 37 0.3× 37 0.3× 59 1.6k
Michael Dörr Germany 23 919 2.4× 782 3.2× 181 0.8× 68 0.6× 642 6.0× 93 2.0k
Cong Yu China 25 1.8k 4.7× 92 0.4× 208 0.9× 85 0.8× 41 0.4× 86 2.1k
Constantin A. Rothkopf Germany 18 796 2.1× 361 1.5× 84 0.4× 102 0.9× 274 2.6× 70 1.3k
S. P. Arun India 16 614 1.6× 149 0.6× 98 0.4× 41 0.4× 19 0.2× 50 762
John A. Greenwood United Kingdom 23 1.2k 3.1× 195 0.8× 129 0.6× 62 0.6× 32 0.3× 68 1.8k
Adrien Baranès France 9 335 0.9× 64 0.3× 249 1.1× 193 1.8× 29 0.3× 12 895

Countries citing papers authored by Adam M. Larson

Since Specialization
Citations

This map shows the geographic impact of Adam M. Larson'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 Adam M. Larson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam M. Larson more than expected).

Fields of papers citing papers by Adam M. Larson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adam M. Larson. 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 Adam M. Larson. The network helps show where Adam M. Larson may publish in the future.

Co-authorship network of co-authors of Adam M. Larson

This figure shows the co-authorship network connecting the top 25 collaborators of Adam M. Larson. A scholar is included among the top collaborators of Adam M. Larson 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 Adam M. Larson. Adam M. Larson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Feldman, Daniel, Keith Jones, Jason H. Huang, et al.. (2023). 18. Short-Term Mood Effects of Repeated Propofol Infusions for Depression. Biological Psychiatry. 93(9). S101–S101.
2.
Jones, Keith, Matthew J. Euler, Jason H. Huang, et al.. (2023). Diversity of electroencephalographic patterns during propofol-induced burst suppression. Frontiers in Systems Neuroscience. 17. 1172856–1172856. 6 indexed citations
3.
Magliano, Joseph P., et al.. (2015). The relative roles of visuospatial and linguistic working memory systems in generating inferences during visual narrative comprehension. Memory & Cognition. 44(2). 207–219. 63 indexed citations
4.
Larson, Adam M., et al.. (2015). An efficient circuit model for design of synchronous machines. 1. 84–89.
5.
Loschky, Lester C., Adam M. Larson, Joseph P. Magliano, & Tim J. Smith. (2014). What Would Jaws Do? The tyranny of film and the relationship between gaze and higher-level comprehension processes for narrative film.. Journal of Vision. 14(10). 761–761. 1 indexed citations
6.
7.
Larson, Adam M., et al.. (2014). Can Visual Cues and Correctness Feedback Influence Students' Reasoning?. The Physics Video Demonstration Database (Cornell University). 305–308. 3 indexed citations
8.
Ringer, Robert, et al.. (2014). Investigating visual crowding of objects in complex scene images. Journal of Vision. 14(10). 779–779. 1 indexed citations
9.
Larson, Adam M., et al.. (2014). Influence of visual cueing on students' eye movements while solving physics problems. 191–194. 3 indexed citations
10.
Pannasch, Sebastian, Jens R. Helmert, Bruce C. Hansen, Adam M. Larson, & Lester C. Loschky. (2013). Characteristics of ambient and focal processing during the visual exploration of aerial and terrestrial scenes. Journal of Vision. 13(9). 1207–1207. 1 indexed citations
11.
Larson, Adam M., et al.. (2013). The spatiotemporal dynamics of scene gist recognition.. Journal of Experimental Psychology Human Perception & Performance. 40(2). 471–487. 42 indexed citations
12.
Larson, Adam M., et al.. (2012). Scene Gist Meets Event Perception: The Time Course of Scene Gist and Event Recognition. Journal of Vision. 12(9). 1077–1077. 4 indexed citations
13.
Mancuso, James J., Adam M. Larson, Theodore G. Wensel, & Peter Saggau. (2009). Multiphoton adaptation of a commercial low-cost confocal microscope for live tissue imaging. Journal of Biomedical Optics. 14(3). 34048–34048. 12 indexed citations
14.
Larson, Adam M. & Lester C. Loschky. (2009). The contributions of central versus peripheral vision to scene gist recognition. Journal of Vision. 9(10). 6–6. 192 indexed citations
15.
Yeh, Alvin T., et al.. (2008). Advances in Nonlinear Optical Microscopy for Visualizing Dynamic Tissue Properties in Culture. Tissue Engineering Part B Reviews. 14(1). 119–131. 20 indexed citations
16.
Larson, Adam M. & Alvin T. Yeh. (2008). Delivery of sub-10-fs pulses for nonlinear optical microscopy by polarization-maintaining single mode optical fiber. Optics Express. 16(19). 14723–14723. 16 indexed citations
17.
Loschky, Lester C. & Adam M. Larson. (2008). Localized information is necessary for scene categorization, including the Natural/Man-made distinction. Journal of Vision. 8(1). 4–4. 36 indexed citations
18.
Larson, Adam M. & Alvin T. Yeh. (2006). Ex vivo characterization of sub-10-fs pulses. Optics Letters. 31(11). 1681–1681. 38 indexed citations
19.
Iyer, V., et al.. (2005). Acousto-optic multiphoton laser scanning microscopy (AO-MPLSM) for structural and functional imaging in living brain slices. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5700. 90–90. 7 indexed citations
20.
Larson, Adam M., et al.. (2004). Efficient fiber-coupled detection for multiphoton microscopy: characterization and comparison with air-coupled detection. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5323. 415–415. 1 indexed citations

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.

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