S. P. Arun

1.4k total citations
50 papers, 762 citations indexed

About

S. P. Arun is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, S. P. Arun has authored 50 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Cognitive Neuroscience, 15 papers in Computer Vision and Pattern Recognition and 5 papers in Artificial Intelligence. Recurrent topics in S. P. Arun's work include Visual perception and processing mechanisms (25 papers), Neural dynamics and brain function (18 papers) and Face Recognition and Perception (17 papers). S. P. Arun is often cited by papers focused on Visual perception and processing mechanisms (25 papers), Neural dynamics and brain function (18 papers) and Face Recognition and Perception (17 papers). S. P. Arun collaborates with scholars based in India, United States and Netherlands. S. P. Arun's co-authors include Sliman J. Bensmaı̈a, R. T. Pramod, Kenneth O. Johnson, Carl R. Olson, Harish Katti, N. Apurva Ratan Murty, Sung Soo Kim, Takashi Yoshioka, Steven S. Hsiao and Kirtimaan A. Mohan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

S. P. Arun

49 papers receiving 751 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. P. Arun India	16	614	149	110	98	66	50	762
Yoichi Miyawaki Japan	10	730 1.2×	130 0.9×	68 0.6×	79 0.8×	21 0.3×	25	886
Grace W. Lindsay United States	7	505 0.8×	135 0.9×	159 1.4×	57 0.6×	22 0.3×	11	838
Johnson Thie Australia	10	379 0.6×	63 0.4×	100 0.9×	90 0.9×	21 0.3×	18	676
Rishi Rajalingham United States	10	339 0.6×	118 0.8×	64 0.6×	20 0.2×	28 0.4×	15	492
Naokazu Goda Japan	18	954 1.6×	72 0.5×	73 0.7×	166 1.7×	32 0.5×	30	1.1k
William A. Simpson United Kingdom	17	472 0.8×	69 0.5×	44 0.4×	73 0.7×	47 0.7×	63	840
Matthias Nau Germany	10	435 0.7×	84 0.6×	87 0.8×	31 0.3×	14 0.2×	17	538
Ethan M. Meyers United States	13	1.1k 1.7×	258 1.7×	126 1.1×	135 1.4×	14 0.2×	20	1.3k
Michael D. Howard United States	9	186 0.3×	125 0.8×	78 0.7×	26 0.3×	47 0.7×	23	585
Hiroshi Ando Japan	16	360 0.6×	129 0.9×	121 1.1×	71 0.7×	55 0.8×	86	731

Countries citing papers authored by S. P. Arun

Since Specialization

Citations

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

Fields of papers citing papers by S. P. Arun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. P. Arun. 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 S. P. Arun. The network helps show where S. P. Arun may publish in the future.

Co-authorship network of co-authors of S. P. Arun

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Arun, S. P.. (2022). Using compositionality to understand parts in whole objects. European Journal of Neuroscience. 56(4). 4378–4392. 5 indexed citations

Katti, Harish & S. P. Arun. (2022). A separable neural code in monkey IT enables perfect CAPTCHA decoding. Journal of Neurophysiology. 127(4). 869–884. 2 indexed citations

Pramod, R. T., Harish Katti, & S. P. Arun. (2022). Human peripheral blur is optimal for object recognition. Vision Research. 200. 108083–108083. 5 indexed citations

Arun, S. P., et al.. (2022). The Bouba–Kiki effect is predicted by sound properties but not speech properties. Attention Perception & Psychophysics. 86(3). 976–990. 7 indexed citations

Nag, Sonali, et al.. (2022). Letter processing in upright bigrams predicts reading fluency variations in children.. Journal of Experimental Psychology General. 151(9). 2237–2249. 3 indexed citations

Pramod, R. T., et al.. (2021). Qualitative similarities and differences in visual object representations between brains and deep networks. Nature Communications. 12(1). 1872–1872. 60 indexed citations

Shashidhara, Sneha, et al.. (2020). Perceptual Priming Can Increase or Decrease With Aging. Frontiers in Aging Neuroscience. 12. 576922–576922. 1 indexed citations

Arun, S. P., et al.. (2019). Reading Increases the Compositionality of Visual Word Representations. Psychological Science. 30(12). 1707–1723. 15 indexed citations

Katti, Harish, Marius V. Peelen, & S. P. Arun. (2019). Machine vision benefits from human contextual expectations. Scientific Reports. 9(1). 2112–2112. 9 indexed citations

10.

Murty, N. Apurva Ratan & S. P. Arun. (2017). A Balanced Comparison of Object Invariances in Monkey IT Neurons. eNeuro. 4(2). ENEURO.0333–16.2017. 11 indexed citations

11.

Katti, Harish, Marius V. Peelen, & S. P. Arun. (2016). Object detection can be improved using human-derived contextual expectations. arXiv (Cornell University). 1 indexed citations

12.

Arun, S. P., et al.. (2016). A neural substrate for object permanence in monkey inferotemporal cortex. Scientific Reports. 6(1). 30808–30808. 4 indexed citations

13.

Pramod, R. T. & S. P. Arun. (2014). Features in visual search combine linearly. Journal of Vision. 14(4). 6–6. 16 indexed citations

14.

Arun, S. P., et al.. (2013). Does linear separability really matter? Complex visual search is explained by simple search. Journal of Vision. 13(11). 10–10. 19 indexed citations

15.

Arun, S. P.. (2012). Turning visual search time on its head. Vision Research. 74. 86–92. 22 indexed citations

16.

Mohan, Kirtimaan A. & S. P. Arun. (2012). Similarity relations in visual search predict rapid visual categorization. Journal of Vision. 12(11). 19–19. 21 indexed citations

17.

Arun, S. P. & Carl R. Olson. (2010). Global Image Dissimilarity in Macaque Inferotemporal Cortex Predicts Human Visual Search Efficiency. Journal of Neuroscience. 30(4). 1258–1269. 24 indexed citations

18.

Arun, S. P. & Carl R. Olson. (2010). Responses to Compound Objects in Monkey Inferotemporal Cortex: The Whole Is Equal to the Sum of the Discrete Parts. Journal of Neuroscience. 30(23). 7948–7960. 26 indexed citations

19.

Arun, S. P., et al.. (2006). Spatiotemporal Receptive Fields of Peripheral Afferents and Cortical Area 3b and 1 Neurons in the Primate Somatosensory System. Journal of Neuroscience. 26(7). 2101–2114. 67 indexed citations

20.

Arun, S. P., Sliman J. Bensmaı̈a, & Kenneth O. Johnson. (2006). A Continuum Mechanical Model of Mechanoreceptive Afferent Responses to Indented Spatial Patterns. Journal of Neurophysiology. 95(6). 3852–3864. 91 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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