Khaled Daqrouq

1.4k citations
63 papers · 1.1k · h-index 15

Impact in

Papers in

Khaled Daqrouq

56 papers receiving 1.0k citations

Peers

Khaled Daqrouq
Comparison fields: 5 of 97
  • Signal Processing 390
  • Cardiology and Cardiovascular Medicine 320
  • Artificial Intelligence 356
  • Physiology 222
  • Computer Vision and Pattern Recognition 202
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Karthikeyan Umapathy Canada
Manuel Blanco–Velasco Spain
Behnaz Ghoraani United States
Kuang Chua Chua Singapore
Ahmed Hammouch Morocco
S. Shahnawazuddin India
Zhao Ren Germany
S.M. Panas Greece
Szu‐Wei Fu Taiwan
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Citations per field
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Citations per year

Countries citing papers authored by Khaled Daqrouq

Since Specialization
Citations

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

Fields of papers citing papers by Khaled Daqrouq

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008318
2 2016162
3 2015104
4 201455
5 201143
6 201237
7 201434
8 201728
9 201326
10 202225
11 201722
12 201521
13 201020
14 202118
15 202215
16 201612
17 201312
18 202211
19 200810
20 201010

About Khaled Daqrouq

Khaled Daqrouq is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine and Control and Systems Engineering, having authored 63 papers that have together received 1.1k indexed citations. Recurring topics across this work include Speech and Audio Processing (26 papers), Speech Recognition and Synthesis (23 papers), ECG Monitoring and Analysis (13 papers), Blind Source Separation Techniques (12 papers), Music and Audio Processing (7 papers), EEG and Brain-Computer Interfaces (5 papers), Fault Detection and Control Systems (5 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Signal Processing (390 citations), Cardiology and Cardiovascular Medicine (320 citations), Artificial Intelligence (356 citations), Physiology (222 citations) and Computer Vision and Pattern Recognition (202 citations). Khaled Daqrouq has collaborated with scholars based in Saudi Arabia, Jordan and Germany. Frequent co-authors include Mikhled Alfaouri, Juan Rafael Orozco‐Arroyave, Julián D. Arias-Londoño, Florian Hönig, Jan Rusz, Elmar Nöth, J. F. Vargas‐Bonilla, Sabine Skodda, Tarek A. Tutunji and Ali Morfeq. Their work appears in journals such as Journal of Applied Sciences, American Journal of Applied Sciences, Applied Soft Computing, Applied Physics Letters and The Journal of the Acoustical Society of America.

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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