Pavel Pudil

5.6k total citations · 1 hit paper
63 papers, 3.5k citations indexed

About

Pavel Pudil is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Strategy and Management. According to data from OpenAlex, Pavel Pudil has authored 63 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 9 papers in Strategy and Management. Recurrent topics in Pavel Pudil's work include Neural Networks and Applications (18 papers), Face and Expression Recognition (15 papers) and Bayesian Methods and Mixture Models (7 papers). Pavel Pudil is often cited by papers focused on Neural Networks and Applications (18 papers), Face and Expression Recognition (15 papers) and Bayesian Methods and Mixture Models (7 papers). Pavel Pudil collaborates with scholars based in Czechia, United Kingdom and Spain. Pavel Pudil's co-authors include Jana Novovičová, Josef Kittler, Petr Somol, Pavel Paclı́k, Francesc J. Ferri, Jan Vanthienen, Bart Baesens, Michal Haindl, Lenka Komárková and Adnan Amin and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition.

In The Last Decade

Pavel Pudil

56 papers receiving 3.3k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Floating search methods in feature selection

1994 2.2k citations Pavel Pudil, Jana Novovičová et al. Pattern Recognition Letters profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pavel Pudil Czechia	15	1.5k	1.3k	417	416	358	63	3.5k
Jana Novovičová Czechia	14	1.3k 0.9×	1.2k 1.0×	405 1.0×	389 0.9×	381 1.1×	29	3.3k
P. A. Estévez Chile	28	1.4k 0.9×	923 0.7×	290 0.7×	394 0.9×	178 0.5×	131	3.5k
Ruby C. Weng Taiwan	11	1.3k 0.9×	1.1k 0.9×	294 0.7×	317 0.8×	387 1.1×	24	3.2k
Tuan D. Pham Australia	33	1.2k 0.8×	1.2k 0.9×	433 1.0×	432 1.0×	255 0.7×	295	4.2k
Ethem Alpaydın Türkiye	24	1.6k 1.1×	1.3k 1.0×	291 0.7×	293 0.7×	263 0.7×	80	3.1k
S.R. Gunn United Kingdom	16	1.3k 0.9×	1.1k 0.9×	352 0.8×	362 0.9×	543 1.5×	41	4.4k
Wang Xiang-rui China	3	2.6k 1.7×	1.8k 1.4×	460 1.1×	444 1.1×	237 0.7×	12	4.8k
Weibo Liu China	29	2.0k 1.4×	1.6k 1.2×	193 0.5×	297 0.7×	248 0.7×	95	5.9k
Preetha Phillips United States	34	1.3k 0.9×	1.4k 1.1×	180 0.4×	202 0.5×	243 0.7×	58	4.0k
Mika Sirén Germany	12	2.4k 1.6×	2.8k 2.2×	578 1.4×	776 1.9×	576 1.6×	17	5.9k

Countries citing papers authored by Pavel Pudil

Since Specialization

Citations

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

Fields of papers citing papers by Pavel Pudil

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavel Pudil

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Pudil. A scholar is included among the top collaborators of Pavel Pudil 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 Pavel Pudil. Pavel Pudil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Pudil, Pavel, et al.. (2021). FURTHER EDUCATION, ITS METHODS AND SELECTED CHARACTERISTICS OF ORGANISATIONS: AN EMPIRICAL STUDY OF THEIR ASSOCIATION WITH ORGANISATIONS PROFITABILITY. SHILAP Revista de lepidopterología. 19(1). 111–130. 1 indexed citations

Pudil, Pavel, et al.. (2019). Relation of selected factors of further education in organizations development and profitability of organizations. 2 indexed citations

Komárková, Lenka, et al.. (2019). Support of development of non-profit organisations through special training programs for their managers. 3 indexed citations

Komárková, Lenka, et al.. (2014). The Factors and Other Characteristics Influencing Competitiveness of Enterprises in Countries in the Post-Transition Phase of the Economy. Engineering Economics. 25(5). 513–521. 4 indexed citations

Pudil, Pavel, et al.. (2013). Identification of Corporate Competitiveness Factors – Comparing Different Approaches. ASEP. 259–267. 1 indexed citations

Somol, Petr, et al.. (2011). Improving feature selection process resistance to failures caused by curse-of-dimensionality effects. Kybernetika. 47(3). 401–425. 4 indexed citations

Somol, Petr, et al.. (2010). Statistical Model of the 2001 Czech Census for Interactive Presentation. Journal of Official Statistics. 26(4). 673–694. 2 indexed citations

Novovičová, Jana, Petr Somol, & Pavel Pudil. (2009). A New Measure of Feature Selection Algorithms' Stability. 4673. 382–387. 6 indexed citations

Somol, Petr, et al.. (2008). TEXTURE ORIENTED IMAGE INPAINTING BASED ON LOCAL STATISTICAL MODEL. 3 indexed citations

10.

Somol, Petr, Jana Novovičová, & Pavel Pudil. (2007). NOTES ON THE EVOLUTION OF FEATURE SELECTION METHODOLOGY. Kybernetika. 43(5). 713–730. 9 indexed citations

11.

Somol, Petr & Pavel Pudil. (2006). Multi-Subset Selection for Keyword Extraction and Other Prototype Search Tasks Using Feature Selection Algorithms. 736–739. 2 indexed citations

12.

Somol, Petr, et al.. (2005). Probabilistic neural network playing and learning Tic–Tac–Toe. Pattern Recognition Letters. 26(12). 1866–1873. 5 indexed citations

13.

Pudil, Pavel, et al.. (2003). Boosting in probabilistic neural networks. 2. 136–139. 3 indexed citations

14.

Pudil, Pavel, Jana Novovičová, & Petr Somol. (2002). Feature selection toolbox software package. Pattern Recognition Letters. 23(4). 487–492. 19 indexed citations

15.

Somol, Petr & Pavel Pudil. (2002). Oscillating search algorithms for feature selection. 2. 406–409. 39 indexed citations

16.

Somol, Petr & Pavel Pudil. (2001). Feature Selection Toolbox as a Multi-Purpose Tool in Pattern Recognition. 91–102. 1 indexed citations

17.

Pudil, Pavel, et al.. (1998). Conceptual base of feature selection consulting system.. Kybernetika. 34(4). 451–460. 1 indexed citations

18.

Novovičová, Jana, Pavel Pudil, & Josef Kittler. (1996). Divergence based feature selection for multimodal class densities. IEEE Transactions on Pattern Analysis and Machine Intelligence. 18(2). 218–223. 66 indexed citations

19.

Pudil, Pavel, et al.. (1991). Statistical approach to pattern recognition: Theory and practical solution by means of PREDITAS system. Kybernetika. 27(7). 1–11. 18 indexed citations

20.

Pudil, Pavel, et al.. (1981). Evaluation of the effectiveness of features selected by discriminant analysis methods. Pattern Recognition. 14(1-6). 81–85. 1 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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