A. J. Ahumada

30 papers receiving 634 citations

Peers

A. J. Ahumada
Comparison fields: 5 of 89
  • Cognitive Neuroscience 395
  • Computer Vision and Pattern Recognition 236
  • Cellular and Molecular Neuroscience 73
  • Atomic and Molecular Physics, and Optics 72
  • Media Technology 66
Replace Sunanda Mitra with:
Sunanda Mitra United States
Dahlia Sharon Israel
Joachim Böttger Germany
Craig R. Schwartz United States
A. Dobbins United States
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P.C. Teo United States
Christopher W. Tyler United States
R. Frank Quick United States
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A. J. Ahumada relative to Sunanda Mitra United States Sunanda Mitra's profile →
Citations per field
00.5×3.6×
Sunanda Mitra · 1×
Citations per year

Countries citing papers authored by A. J. Ahumada

Since Specialization
Citations

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

Fields of papers citing papers by A. J. Ahumada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. J. Ahumada. 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 A. J. Ahumada. The network helps show where A. J. Ahumada may publish in the future.

Co-authorship network of co-authors of A. J. Ahumada

This figure shows the co-authorship network connecting the top 25 collaborators of A. J. Ahumada. A scholar is included among the top collaborators of A. J. Ahumada 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 A. J. Ahumada. A. J. Ahumada 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
#WorkIndexed citations
1 14
2 2
3 0
4
Spatial Integration and the Neural Transfer Function
1
5 0
6 1
7 4
8
Predicting Acuity From Aberrations With the Spatial Standard Observer
1
9
A spatial standard observer based on contrast energy
1
10 7
11
Image Discrimination Models for Object Detection in Natural Backgrounds
0
12 1
13 2
14 119
15
Smoothing DCT Compression Artifacts
10
16
The Visibility of DCT Quantization Noise: Spatial Frequency Summation
8
17
Learning by assertion: A method for calibrating a simple visual system
3
18 57
19 175
20 1

About A. J. Ahumada

A. J. Ahumada is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Media Technology, having authored 36 papers that have together received 676 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (17 papers), Color Science and Applications (9 papers) and Infrared Target Detection Methodologies (8 papers). The work is most often cited by research in Cognitive Neuroscience (395 citations), Computer Vision and Pattern Recognition (236 citations) and Media Technology (66 citations). A. J. Ahumada has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Andrew B. Watson, Terry L. Jernigan, James Larimer, Misha Pavel, Joshua A. Solomon, Bettina L. Beard, Lauren Scharff, Laurence T. Maloney, Heidi A. Peterson and Andrew Watson. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Biomedical Engineering and Investigative Ophthalmology & Visual Science.

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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