Jakub Nalepa

251 total papers · 3.8k total citations
119 papers, 2.2k citations indexed

About

Jakub Nalepa is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Jakub Nalepa has authored 119 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computer Vision and Pattern Recognition, 43 papers in Artificial Intelligence and 40 papers in Media Technology. Recurrent topics in Jakub Nalepa's work include Remote-Sensing Image Classification (30 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Advanced Image Fusion Techniques (19 papers). Jakub Nalepa is often cited by papers focused on Remote-Sensing Image Classification (30 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Advanced Image Fusion Techniques (19 papers). Jakub Nalepa collaborates with scholars based in Poland, Italy and Switzerland. Jakub Nalepa's co-authors include Michał Kawulok, Pablo Ribalta Lorenzo, Michał Myller, Michał Marcinkiewicz, Luciano Sánchez, José Ranilla, Daniel Kostrzewa, Bogdan Smołka, Nicolas Longépé and Bertrand Le Saux and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.

In The Last Decade

Jakub Nalepa

111 papers receiving 2.1k citations

Hit Papers

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Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jakub Nalepa 845 660 559 201 200 119 2.2k
Michał Kawulok 920 1.1× 463 0.7× 400 0.7× 115 0.6× 164 0.8× 91 1.9k
Khurram Khurshid 942 1.1× 447 0.7× 605 1.1× 179 0.9× 241 1.2× 87 2.0k
Zhixi Feng 953 1.1× 561 0.8× 606 1.1× 209 1.0× 105 0.5× 93 2.2k
Xu Liu 1.2k 1.4× 639 1.0× 842 1.5× 257 1.3× 222 1.1× 223 2.9k
Haikel Alhichri 868 1.0× 620 0.9× 816 1.5× 321 1.6× 107 0.5× 71 2.5k
S. Arivazhagan 1.1k 1.2× 239 0.4× 493 0.9× 105 0.5× 78 0.4× 141 1.9k
Chih‐Cheng Hung 584 0.7× 430 0.7× 375 0.7× 190 0.9× 377 1.9× 130 1.7k
Liejun Wang 827 1.0× 432 0.7× 525 0.9× 262 1.3× 194 1.0× 170 1.9k
Sheifali Gupta 510 0.6× 579 0.9× 186 0.3× 128 0.6× 392 2.0× 303 2.4k
Roberto Lotufo 1.7k 2.0× 575 0.9× 413 0.7× 173 0.9× 445 2.2× 134 3.1k

Countries citing papers authored by Jakub Nalepa

Since Specialization
Citations

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

Fields of papers citing papers by Jakub Nalepa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jakub Nalepa

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

All Works

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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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