Kamal Al‐Sabahi

767 citations
11 papers · 518 indexed · 1 hit paper · h-index 6
Topics
Topic Modeling (8 papers)Natural Language Processing Techniques (7 papers)Advanced Text Analysis Techniques (5 papers)
Partner nations
ChinaYemenOman

In The Last Decade

Kamal Al‐Sabahi

10 papers receiving 494 citations

Hit Papers

Deep Learning Approach Combining Sparse Autoencoder With ...20182026202020232018100200300

Peers

Kamal Al‐Sabahi
Comparison fields: 5 of 59
  • Artificial Intelligence 429
  • Computer Networks and Communications 313
  • Signal Processing 179
  • Information Systems 41
  • Control and Systems Engineering 32
Replace İlhan Fırat Kılınçer with:
İlhan Fırat Kılınçer Türkiye
Yazan Otoum Canada
Majjed Al-Qatf China
Jiancheng Qin China
Ly Vu Vietnam
Xuehui Du China
Gözde Karataş Türkiye
Srilatha Chebrolu India
Yulong Fu China
Kamal Al‐Sabahi relative to İlhan Fırat Kılınçer Türkiye İlhan Fırat Kılınçer's profile →
Citations per field
00.5×10×15×19.5×
İlhan Fırat Kılınçer · 1×
Citations per year

Countries citing papers authored by Kamal Al‐Sabahi

Since Specialization
Citations

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

Fields of papers citing papers by Kamal Al‐Sabahi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kamal Al‐Sabahi. 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 Kamal Al‐Sabahi. The network helps show where Kamal Al‐Sabahi may publish in the future.

Co-authorship network of co-authors of Kamal Al‐Sabahi

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 0
2 1
3 4
4 19
5 8
6 5
7 2
8 9
9
Deep Learning Approach Combining Sparse Autoencoder With SVM for Network Intrusion Detectionbreakdown →
364
10 93
11 13

About Kamal Al‐Sabahi

Kamal Al‐Sabahi is a scholar working on Artificial Intelligence, Signal Processing and Information Systems, having authored 11 papers that have together received 518 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers) and Advanced Text Analysis Techniques (5 papers). The work is most often cited by research in Signal Processing (179 citations), Computer Networks and Communications (313 citations) and Artificial Intelligence (429 citations). Kamal Al‐Sabahi has collaborated with scholars based in China, Yemen and Oman. Frequent co-authors include Mohammed Al‐Habib, Majjed Al-Qatf, Lasheng Yu, Zuping Zhang, Kang Yang, Farida Mohsen, Jiayang Wang, Xian Li, Yao Lu and Xinjun Mao. Their work appears in journals such as IEEE Access, Engineering Applications of Artificial Intelligence and Applied 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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