G. Barna

706 citations
13 papers · 509 indexed · h-index 8

G. Barna

12 papers receiving 445 citations

Peers

G. Barna
Comparison fields: 5 of 85
  • Artificial Intelligence 275
  • Signal Processing 87
  • Statistical and Nonlinear Physics 76
  • Computer Vision and Pattern Recognition 116
  • Cognitive Neuroscience 97
Replace Stergios Papadimitriou with:
Stergios Papadimitriou Greece
Françoise Fogelman Soulié France
Malte Kuß Germany
S. Amari Japan
István Dénes Germany
M.A. Jabri Australia
Yasuo Matsuyama Japan
C. Gielen Netherlands
António R. C. Paiva United States
G. Barna relative to Stergios Papadimitriou Greece Stergios Papadimitriou's profile →
Citations per field
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Stergios Papadimitriou · 1×
Citations per year

Countries citing papers authored by G. Barna

Since Specialization
Citations

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

Fields of papers citing papers by G. Barna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 13 scholars most cited alongside G. Barna, 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 G. Barna Line = papers co-authored together G. Barna links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20022
2 19995
3 199819
4 199815
5
Multicompartmental modeling of hippocampal pyramidal cells and interneurons with the GENESIS software tool.
19960
6 19951
7 199541
8 199330
9 199345
10 19907
11 19897
12 198827
13
Statistical pattern recognition with neural networks: benchmarking studies.
1988310

About G. Barna

G. Barna is a scholar working on Sensory Systems, Statistical and Nonlinear Physics, Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 509 indexed citations. Recurring topics across this work include Neural dynamics and brain function (4 papers), Neural Networks and Applications (4 papers), Olfactory and Sensory Function Studies (3 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Neuroscience and Neuropharmacology Research (2 papers), Chaos control and synchronization (2 papers), stochastic dynamics and bifurcation (2 papers) and Complex Systems and Time Series Analysis (2 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Signal Processing (87 citations), Statistical and Nonlinear Physics (76 citations), Computer Vision and Pattern Recognition (116 citations) and Cognitive Neuroscience (97 citations). G. Barna has collaborated with scholars based in Hungary, Japan and Germany. Frequent co-authors include Ron Chrisley, Teuvo Kohonen, P. Érdi, Ichiro Tsuda, Kimmo Kaski, Ildikó Aradi, Trienko Grobler, Péter Érdi, Péter Adorján and Klaus Obermayer. Their work appears in journals such as Biological Cybernetics, International Journal of Intelligent Systems, Physics Letters A, Neural Networks 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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