Michal Sofka

1.6k citations
42 papers · 1.3k · h-index 19

Impact in

Papers in

Michal Sofka

41 papers receiving 1.3k citations

Peers

Michal Sofka
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 606
  • Health Informatics 56
  • Radiology, Nuclear Medicine and Imaging 497
  • Signal Processing 57
  • Biophysics 34
Replace Denis P. Friboulet with:
Denis P. Friboulet France
Jingfan Fan China
Emanuele Torti Italy
Il Dong Yun South Korea
Regev Cohen Israel
Hidefumi Kobatake Japan
Fahad Shamshad United Arab Emirates
Yongbum Lee Japan
Satoshi Kondo Japan
Amirhossein Kazerouni Iran
Michal Sofka relative to Denis P. Friboulet France Denis P. Friboulet's profile →
Citations per field
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Citations per year

Countries citing papers authored by Michal Sofka

Since Specialization
Citations

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

Fields of papers citing papers by Michal Sofka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michal Sofka, 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 Michal Sofka Line = papers co-authored together Michal Sofka links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006275
2 2007213
3 200781
4
Optimized invariant representation of network traffic for detecting unseen malware variants
201676
5 202351
6 202250
7 201148
8 201148
9 202242
10 201733
11 200731
12 201431
13 201327
14 200824
15 201423
16 201923
17 201720
18 201019
19 201219
20 201519

About Michal Sofka

Michal Sofka is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Signal Processing, Computer Networks and Communications and Health Informatics, having authored 42 papers that have together received 1.3k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (21 papers), Advanced MRI Techniques and Applications (5 papers), Advanced Image and Video Retrieval Techniques (4 papers), Network Security and Intrusion Detection (4 papers), Retinal Imaging and Analysis (4 papers), Advanced Neural Network Applications (3 papers), Advanced Malware Detection Techniques (3 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (606 citations), Health Informatics (56 citations), Radiology, Nuclear Medicine and Imaging (497 citations), Signal Processing (57 citations) and Biophysics (34 citations). Michal Sofka has collaborated with scholars based in United States, Germany and Taiwan. Frequent co-authors include Charles V. Stewart, G. Yang, Chia-Ling Tsai, Shaohua Kevin Zhou, Vojtěch Franc, Jingdan Zhang, Neil Birkbeck, Fausto Milletarì, Seyed Sadegh Mohseni Salehi and Jo Schlemper. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Medical Imaging, Lecture notes in computer science, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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