Saiful Akbar

448 citations
85 papers · 296 · h-index 8

Impact in

Papers in

Saiful Akbar

73 papers receiving 285 citations

Peers

Saiful Akbar
Comparison fields: 5 of 86
  • Signal Processing 41
  • Information Systems 85
  • Transportation 23
  • Artificial Intelligence 109
  • Computer Vision and Pattern Recognition 64
Replace Panos Kostakos with:
Panos Kostakos Finland
Raquel Trillo-Lado Spain
Mohammad Shamsul Arefin Bangladesh
Radu Mariescu-Istodor Finland
Asif Iqbal Baba United States
Sujala D. Shetty United Arab Emirates
J. Javier Samper Spain
Zefeng Chen China
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Citations per field
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Citations per year

Countries citing papers authored by Saiful Akbar

Since Specialization
Citations

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

Fields of papers citing papers by Saiful Akbar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202150
2 201416
3 201611
4 201410
5 20248
6 20198
7 20178
8 20227
9 20187
10 20186
11 20176
12 20206
13 20116
14 20146
15 20166
16 20176
17 20145
18 20175
19 20175
20 20155

About Saiful Akbar

Saiful Akbar is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 85 papers that have together received 296 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (9 papers), Advanced Text Analysis Techniques (8 papers), Web Data Mining and Analysis (8 papers), Biometric Identification and Security (7 papers), Service-Oriented Architecture and Web Services (7 papers), Data Quality and Management (7 papers), Image Retrieval and Classification Techniques (7 papers) and Data Management and Algorithms (6 papers). The work is most often cited by research in Signal Processing (41 citations), Information Systems (85 citations), Transportation (23 citations), Artificial Intelligence (109 citations) and Computer Vision and Pattern Recognition (64 citations). Saiful Akbar has collaborated with scholars based in Indonesia, Austria and Sri Lanka. Frequent co-authors include Benhard Sitohang, Masayu Leylia Khodra, Gede Indrawan, Wikan Danar Sunindyo, Fajar J. Ekaputra, Yudistira Asnar, Laura Slaughter, Øystein Nytrø, Roland Wagner and Dwi H. Widyantoro. Their work appears in journals such as Journal of Multimedia, IEEE Access, ISPRS International Journal of Geo-Information, Viruses and International Journal of Paediatric Dentistry.

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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