Eizaburo Doi

415 citations
10 papers · 250 · h-index 9

Impact in

Papers in

Eizaburo Doi

10 papers receiving 242 citations

Peers

Eizaburo Doi
Comparison fields: 5 of 54
  • Cognitive Neuroscience 183
  • Cellular and Molecular Neuroscience 46
  • Biophysics 13
  • Sensory Systems 10
  • Computer Vision and Pattern Recognition 37
Replace Scott S. Grigsby with:
Scott S. Grigsby United States
Corey M. Ziemba United States
Alexander G. Dimitrov United States
Joseph Sirosh United States
Benjamin D. Haeffele United States
Jason Prentice United States
Kô Sakai Japan
Julie Martin United States
Samuel A. Ellias United States
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Citations per field
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Citations per year

Countries citing papers authored by Eizaburo Doi

Since Specialization
Citations

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

Fields of papers citing papers by Eizaburo Doi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eizaburo Doi. 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 Eizaburo Doi. The network helps show where Eizaburo Doi may publish in the future.

Co-authors

The 18 scholars most cited alongside Eizaburo Doi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eizaburo Doi Line = papers co-authored together Eizaburo Doi links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 201274
2 200354
3 200731
4 201429
5 200716
6
Sparse Coding of Natural Images Using an Overcomplete Set of Limited Capacity Units
200413
7
A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels
200512
8 201111
9
Relations between the statistical regularities of natural images and the response properties of the early visual system
20058
10 20142

About Eizaburo Doi

Eizaburo Doi is a scholar working on Cognitive Neuroscience, Molecular Biology, Signal Processing, Artificial Intelligence and Cellular and Molecular Neuroscience, having authored 10 papers that have together received 250 indexed citations. Recurring topics across this work include Neural dynamics and brain function (7 papers), Retinal Development and Disorders (5 papers), Visual perception and processing mechanisms (4 papers), Neural Networks and Applications (2 papers), Blind Source Separation Techniques (2 papers), Hermeneutics and Narrative Identity (1 paper), Color Science and Applications (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Cognitive Neuroscience (183 citations), Cellular and Molecular Neuroscience (46 citations), Biophysics (13 citations), Sensory Systems (10 citations) and Computer Vision and Pattern Recognition (37 citations). Eizaburo Doi has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Michael S. Lewicki, Thomas Wächtler, Terrence J. Sejnowski, Te-Won Lee, Toshio Inui, A. M. Litke, E. J. Chichilnisky, Greg D. Field, Jonathon Shlens and Eero P. Simoncelli. Their work appears in journals such as Neural Computation, Journal of Vision, IEEE Transactions on Image Processing, Journal of Neuroscience and PLoS Computational Biology.

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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