Vladimı́r Krajča

1.2k total citations
44 papers, 827 citations indexed

About

Vladimı́r Krajča is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Vladimı́r Krajča has authored 44 papers receiving a total of 827 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cognitive Neuroscience, 12 papers in Signal Processing and 10 papers in Artificial Intelligence. Recurrent topics in Vladimı́r Krajča's work include EEG and Brain-Computer Interfaces (23 papers), Functional Brain Connectivity Studies (12 papers) and Blind Source Separation Techniques (10 papers). Vladimı́r Krajča is often cited by papers focused on EEG and Brain-Computer Interfaces (23 papers), Functional Brain Connectivity Studies (12 papers) and Blind Source Separation Techniques (10 papers). Vladimı́r Krajča collaborates with scholars based in Czechia, United States and Slovenia. Vladimı́r Krajča's co-authors include Martin Brunovský, Cyril Höschl, Miloslav Kopeček, Tomáš Novák, P. Šóš, Martin Bareš, M Matouŝek, Pavla Stopková, Jiřı́ Horáček and Alpo Värri and has published in prestigious journals such as Sensors, Clinical Neurophysiology and Journal of Psychiatric Research.

In The Last Decade

Vladimı́r Krajča

40 papers receiving 791 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vladimı́r Krajča Czechia 16 641 136 121 115 110 44 827
Hiroaki Mizuhara Japan 12 646 1.0× 71 0.5× 143 1.2× 61 0.5× 79 0.7× 40 942
Sergio Romero Spain 18 737 1.1× 85 0.6× 172 1.4× 161 1.4× 307 2.8× 61 1.4k
Wojciech Jernajczyk Poland 17 852 1.3× 82 0.6× 54 0.4× 564 4.9× 101 0.9× 56 1.5k
Tracy Warbrick Germany 21 1.2k 1.8× 105 0.8× 35 0.3× 183 1.6× 123 1.1× 49 1.5k
Waldemar Szelenberger Poland 20 681 1.1× 30 0.2× 100 0.8× 346 3.0× 69 0.6× 46 1.1k
Gary Hasey Canada 16 448 0.7× 130 1.0× 30 0.2× 128 1.1× 63 0.6× 40 867
Maria João Rosa United Kingdom 16 1.5k 2.4× 50 0.4× 53 0.4× 326 2.8× 66 0.6× 25 1.8k
Francisco J. Fraga Brazil 18 984 1.5× 30 0.2× 93 0.8× 53 0.5× 159 1.4× 61 1.4k
Michael Grözinger Germany 19 607 0.9× 230 1.7× 50 0.4× 328 2.9× 53 0.5× 65 1.3k
Yuan Chen China 16 465 0.7× 55 0.4× 61 0.5× 138 1.2× 195 1.8× 77 923

Countries citing papers authored by Vladimı́r Krajča

Since Specialization
Citations

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

Fields of papers citing papers by Vladimı́r Krajča

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vladimı́r Krajča

This figure shows the co-authorship network connecting the top 25 collaborators of Vladimı́r Krajča. A scholar is included among the top collaborators of Vladimı́r Krajča 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 Vladimı́r Krajča. Vladimı́r Krajča 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
1.
Brunovský, Martin, et al.. (2019). Artifacts in Simultaneous hdEEG/fMRI Imaging: A Nonlinear Dimensionality Reduction Approach. Sensors. 19(20). 4454–4454. 7 indexed citations
2.
Páleníček, Tomáš, Martin Brunovský, Ingmar Gorman, et al.. (2014). The effect of ((−)-2-oxa-4-aminobicyclo[3.1.0]hexane-2,6-dicarboxylic acid (LY379268), an mGlu2/3 receptor agonist, on EEG power spectra and coherence in ketamine model of psychosis. Pharmacology Biochemistry and Behavior. 122. 212–221. 15 indexed citations
3.
Tichavský, Petr, et al.. (2012). Robust removal of short-duration artifacts in long neonatal EEG recordings using wavelet-enhanced ICA and adaptive combining of tentative reconstructions. Physiological Measurement. 33(8). N39–N49. 40 indexed citations
4.
Páleníček, Tomáš, Martin Brunovský, Marie Balı́ková, et al.. (2011). Electroencephalographic Spectral and Coherence Analysis of Ketamine in Rats: Correlation with Behavioral Effects and Pharmacokinetics. Neuropsychobiology. 63(4). 202–218. 72 indexed citations
5.
Bareš, Martin, Tomáš Novák, Martin Brunovský, et al.. (2011). The change of QEEG prefrontal cordance as a response predictor to antidepressive intervention in bipolar depression. A pilot study. Journal of Psychiatric Research. 46(2). 219–225. 18 indexed citations
6.
Huptych, Michal, et al.. (2010). The Development of Modules for the Support of Education in the field of Biomedical Engineering. Elektronika ir Elektrotechnika. 102(6). 47–50. 3 indexed citations
7.
8.
Brunovský, Martin, Jiřı́ Horáček, Tomáš Novák, et al.. (2008). LORETA Functional Imaging in Antipsychotic-Naive and Olanzapine-, Clozapine- and Risperidone-Treated Patients with Schizophrenia. Neuropsychobiology. 58(1). 1–10. 35 indexed citations
9.
Lhotská, Lenka, et al.. (2008). Multivariate Analysis of Full-Term Neonatal Polysomnographic Data. IEEE Transactions on Information Technology in Biomedicine. 13(1). 104–110. 24 indexed citations
10.
Bareš, Martin, Martin Brunovský, Miloslav Kopeček, et al.. (2008). Early reduction in prefrontal theta QEEG cordance value predicts response to venlafaxine treatment in patients with resistant depressive disorder. European Psychiatry. 23(5). 350–355. 103 indexed citations
11.
Brunovský, Martin, Jiřı́ Horáček, M Matouŝek, et al.. (2008). Trazodone improves the results of cognitive behaviour therapy of primary insomnia in non-depressed patients.. PubMed. 29(6). 895–901. 19 indexed citations
12.
Kopeček, Miloslav, P. Šóš, Martin Bareš, et al.. (2008). QEEG changes during switch from depression to hypomania/mania: a case report.. PubMed. 29(3). 295–302. 10 indexed citations
13.
Horáček, Jiřı́, Martin Brunovský, Tomáš Novák, et al.. (2007). Effect of Low-Frequency rTMS on Electromagnetic Tomography (LORETA) and Regional Brain Metabolism (PET) in Schizophrenia Patients with Auditory Hallucinations. Neuropsychobiology. 55(3-4). 132–142. 89 indexed citations
14.
Krajča, Vladimı́r, et al.. (2006). Quantitative topographic differentiation of the neonatal EEG. Clinical Neurophysiology. 117(9). 2050–2058. 12 indexed citations
15.
Krajča, Vladimı́r, et al.. (2005). Automatic Detection of Sleep Stages in Neonatal EEG Using the Structural Time Profiles. PubMed. 2005. 6014–6016. 18 indexed citations
16.
Krajča, Vladimı́r, et al.. (2003). Comparison of quantitative EEG characteristics of quiet and active sleep in newborns. Sleep Medicine. 4(6). 543–552. 34 indexed citations
17.
Brunovský, Martin, M Matouŝek, Åke Edman, Kateřina Červená, & Vladimı́r Krajča. (2003). Objective Assessment of the Degree of Dementia by Means of EEG. Neuropsychobiology. 48(1). 19–26. 69 indexed citations
18.
Urban, Pavel, et al.. (2002). EEG Photic Driving in Workers Exposed to Mercury Vapors. NeuroToxicology. 24(1). 23–33. 2 indexed citations
19.
Witte, Herbert, et al.. (1991). Use of discrete Hilbert transformation for automatic spike mapping: A methodological investigation. Medical & Biological Engineering & Computing. 29(3). 242–248. 33 indexed citations
20.
Krajča, Vladimı́r, et al.. (1991). Automatic identification of significant graphoelements in multichannel EEG recordings by adaptive segmentation and fuzzy clustering. International Journal of Bio-Medical Computing. 28(1-2). 71–89. 59 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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