Tetsuo Furukawa

40 papers receiving 213 citations

Peers

Tetsuo Furukawa
Comparison fields: 5 of 71
  • Artificial Intelligence 80
  • Computer Vision and Pattern Recognition 56
  • Molecular Biology 48
  • Cellular and Molecular Neuroscience 45
  • Signal Processing 19
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Citations per field
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Citations per year

Countries citing papers authored by Tetsuo Furukawa

Since Specialization
Citations

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

Fields of papers citing papers by Tetsuo Furukawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tetsuo Furukawa

This figure shows the co-authorship network connecting the top 25 collaborators of Tetsuo Furukawa. A scholar is included among the top collaborators of Tetsuo Furukawa 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 Tetsuo Furukawa. Tetsuo Furukawa 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 0
2 10
3 0
4
Tensor Decomposition using Self-Organizing Map and Missing Data Estimation
0
5
Building a cognitive map using an SOM2
0
6
Task segmentation in a mobile robot by mnSOM and clusteringwith spatio-temporal contiguity
3
7 37
8 25
9
SOM of SOMs : An Extension of SOM from 'Map' to 'Homotopy'
2
10
Modular Network SOM: Theory, Algorithm and Applications
1
11
Generalization of the Self-Organizing Map:From Artificial Neural Networks to Artificial Cortexes
1
12 2
13
Improving the Generalization of Fisherface by Training Class Selection Using SOM2
1
14
Modular Network SOM: Self-organizing maps dealing with dynamic systems
1
15 5
16 6
17 10
18
[Basic principles and historical consideration of MR cholangiopancreatography].
0
19 16
20
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision
3

About Tetsuo Furukawa

Tetsuo Furukawa is a scholar working on Computational Mathematics, Artificial Intelligence and Signal Processing, having authored 52 papers that have together received 230 indexed citations. Recurring topics across this work include Neural Networks and Applications (15 papers), Advanced Memory and Neural Computing (6 papers) and Photoreceptor and optogenetics research (5 papers). The work is most often cited by research in Computational Mathematics (5 citations), Computer Vision and Pattern Recognition (56 citations) and Artificial Intelligence (80 citations). Tetsuo Furukawa has collaborated with scholars based in Japan, United Kingdom and Greece. Frequent co-authors include Masahiro Yamada, Mustafa B.A. Djamgoz, Muhammad Aziz Muslim, Shin Yasui, Katsushi Tokunaga, Masumi Ishikawa, Kazuo Ishii, Ove Wigertz, Hiroki Matsumoto and Hiroto Tanaka. Their work appears in journals such as Experimental Brain Research, The Journal of General Physiology and Neurocomputing.

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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