Serkan Günal

42 papers receiving 1.9k citations

Hit Papers

The impact of preprocessing on text classification201320262017202120132018100200300400

Peers

Serkan Günal
Comparison fields: 5 of 140
  • Artificial Intelligence 894
  • Information Systems 487
  • Cardiology and Cardiovascular Medicine 385
  • Computer Vision and Pattern Recognition 363
  • Cognitive Neuroscience 255
Replace Zaid Abdi Alkareem Alyasseri with:
Zaid Abdi Alkareem Alyasseri Iraq
Zhu Wang China
Adi Alhudhaif Saudi Arabia
Mohamed Hammad Egypt
Chan Yeob Yeun United Arab Emirates
Ruggero Donida Labati Italy
Fabio Scotti Italy
Giovanna Castellano Italy
Chastine Fatichah Indonesia
M. F. Mridha Bangladesh
Serkan Günal relative to Zaid Abdi Alkareem Alyasseri Iraq Zaid Abdi Alkareem Alyasseri's profile →
Citations per field
00.5×9.5×
Zaid Abdi Alkareem Alyasseri · 1×
Citations per year

Countries citing papers authored by Serkan Günal

Since Specialization
Citations

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

Fields of papers citing papers by Serkan Günal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serkan Günal

This figure shows the co-authorship network connecting the top 25 collaborators of Serkan Günal. A scholar is included among the top collaborators of Serkan Günal 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 Serkan Günal. Serkan Günal 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
#WorkIndexed citations
1 3
2 1
3 10
4 38
5 50
6 1
7 2
8 7
9
A priori verification and validation study of RFKON database
3
10 3
11 7
12 7
13 5
14 8
15
The impact of preprocessing on text classificationbreakdown →
456
16 46
17 16
18 1
19 2
20 87

About Serkan Günal

Serkan Günal is a scholar working on Signal Processing, Artificial Intelligence and Media Technology, having authored 43 papers that have together received 2.0k indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (9 papers), Text and Document Classification Technologies (9 papers) and Spam and Phishing Detection (7 papers). The work is most often cited by research in Artificial Intelligence (894 citations), Information Systems (487 citations) and Computer Vision and Pattern Recognition (363 citations). Serkan Günal has collaborated with scholars based in Türkiye, United Kingdom and Japan. Frequent co-authors include Alper Kürşat Uysal, Selcan Kaplan Berkaya, Efnan Şora Günal, Semih Ergi̇n, M. Bilginer Gülmezoğlu, Rifat Edizkan, Sinem Bozkurt Keser, Ömer Nezih Gerek, Uğur Yayan and Cüneyt Akınlar. Their work appears in journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Cybernetics.

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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