Refik Samet

69 papers receiving 905 citations

Refik Samet's Hit Papers

A Comprehensive Review on Malware Detection Approaches 2020 · 376 citations
3760+2+4Years since publication100200300

Peers

Refik Samet
Comparison fields: 5 of 82
  • Signal Processing 464
  • Computer Networks and Communications 536
  • Software 53
  • Artificial Intelligence 358
  • Information Systems 237
Replace Xiaochun Yun with:
Xiaochun Yun China
Jingfeng Xue China
Michel Barbeau Canada
Sobia Wassan China
Weiqing Huang China
Levent Ertöz United States
Qiang Huang China
Ming Yang China
Robert S. Gray United States
Refik Samet relative to Xiaochun Yun China Xiaochun Yun's profile →
Citations per field
00.5×3.3×
Xiaochun Yun · 1×
Citations per year

Countries citing papers authored by Refik Samet

Since Specialization
Citations

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

Fields of papers citing papers by Refik Samet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Comprehensive Review on Malware Detection Approaches
Hit paper breakdown →
2020376
2 202188
3 201751
4 202337
5 201737
6 201227
7 201926
8 202017
9 202316
10 201216
11 202116
12 201713
13 201712
14 202212
15 202311
16 201111
17 20189
18
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20089
19 20179
20 20139

About Refik Samet

Refik Samet is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Electrical and Electronic Engineering, having authored 72 papers that have together received 953 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (16 papers), Advanced Malware Detection Techniques (14 papers), AI in cancer detection (8 papers), Medical Image Segmentation Techniques (6 papers), Geophysical Methods and Applications (6 papers), Digital Imaging for Blood Diseases (5 papers), Anomaly Detection Techniques and Applications (5 papers) and Radiation Effects in Electronics (5 papers). The work is most often cited by research in Signal Processing (464 citations), Computer Networks and Communications (536 citations), Software (53 citations), Artificial Intelligence (358 citations) and Information Systems (237 citations). Refik Samet has collaborated with scholars based in Türkiye, New Zealand and Saudi Arabia. Frequent co-authors include Ömer Aslan, Merve Ozkan-Okay, Emrah Hançer, Deepti Gupta, Vitaliy Mezhuyev, Ali Alqahtani, Qasem Abu Al‐Haija, Badraddin Alturki, Abdulaziz A. Alsulami and Ömer Faruk Bay. Their work appears in journals such as IEEE Access, Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, Applied Sciences, Quality and Reliability Engineering International and Biomedical Signal Processing and Control.

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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