Nidal Kamel

3.4k total citations
183 papers, 2.4k citations indexed

About

Nidal Kamel is a scholar working on Cognitive Neuroscience, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nidal Kamel has authored 183 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Cognitive Neuroscience, 44 papers in Signal Processing and 43 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nidal Kamel's work include EEG and Brain-Computer Interfaces (65 papers), Blind Source Separation Techniques (40 papers) and Functional Brain Connectivity Studies (29 papers). Nidal Kamel is often cited by papers focused on EEG and Brain-Computer Interfaces (65 papers), Blind Source Separation Techniques (40 papers) and Functional Brain Connectivity Studies (29 papers). Nidal Kamel collaborates with scholars based in Malaysia, Pakistan and Saudi Arabia. Nidal Kamel's co-authors include Aamir Saeed Malik, Ibrahima Faye, Weng-Tink Chooi, Hafeez Ullah Amin, Muhammad Hussain, Norashikin Yahya, Munsif Ali Jatoi, Rana Fayyaz Ahmad, Wajid Mumtaz and Ahmad Rauf Subhani and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Nidal Kamel

177 papers receiving 2.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nidal Kamel Malaysia 22 1.2k 338 330 323 282 183 2.4k
Aydın Akan Türkiye 25 1.0k 0.8× 430 1.3× 460 1.4× 371 1.1× 462 1.6× 249 2.5k
Enas Abdulhay Jordan 22 772 0.6× 175 0.5× 284 0.9× 292 0.9× 242 0.9× 49 2.1k
Armando Barreto United States 30 940 0.8× 385 1.1× 355 1.1× 478 1.5× 285 1.0× 185 3.2k
Yangsong Zhang China 32 2.3k 1.9× 377 1.1× 254 0.8× 244 0.8× 365 1.3× 100 3.1k
Stéphane Bonnet France 20 1.4k 1.1× 242 0.7× 222 0.7× 160 0.5× 284 1.0× 78 2.2k
Boreom Lee South Korea 29 1.2k 1.0× 155 0.5× 460 1.4× 251 0.8× 257 0.9× 89 2.7k
Alessandro Pasquale De Rosa Portugal 29 2.2k 1.8× 677 2.0× 317 1.0× 321 1.0× 379 1.3× 171 3.9k
Chen Chen China 25 791 0.7× 197 0.6× 174 0.5× 151 0.5× 266 0.9× 186 1.9k
Mohiuddin Ahmad Bangladesh 21 760 0.6× 288 0.9× 351 1.1× 513 1.6× 201 0.7× 169 1.9k
Xi Long Netherlands 28 920 0.8× 326 1.0× 599 1.8× 334 1.0× 216 0.8× 152 2.6k

Countries citing papers authored by Nidal Kamel

Since Specialization
Citations

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

Fields of papers citing papers by Nidal Kamel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nidal Kamel

This figure shows the co-authorship network connecting the top 25 collaborators of Nidal Kamel. A scholar is included among the top collaborators of Nidal Kamel 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 Nidal Kamel. Nidal Kamel 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
1.
Chu, Laurence, et al.. (2024). Functional excitation-inhibition ratio for social anxiety analysis and severity assessment. Frontiers in Psychiatry. 15. 1461290–1461290. 1 indexed citations
2.
Khan, Danish M., Norashikin Yahya, Nidal Kamel, & Ibrahima Faye. (2022). A novel method for efficient estimation of brain effective connectivity in EEG. Computer Methods and Programs in Biomedicine. 228. 107242–107242. 21 indexed citations
3.
Saad, Mohamad Naufal Mohamad, et al.. (2021). Workplace design-related stress effects on prefrontal cortex connectivity and neurovascular coupling. Applied Ergonomics. 96. 103497–103497. 14 indexed citations
4.
Khan, Danish M., et al.. (2020). Effective Connectivity for Default Mode Network Analysis of Alcoholism. Brain Connectivity. 11(1). 12–29. 16 indexed citations
5.
Kamel, Nidal, Aamir Saeed Malik, Sarat C. Dass, et al.. (2018). A study of decoding human brain activities from simultaneous data of EEG and fMRI using MVPA. Australasian Physical & Engineering Sciences in Medicine. 41(3). 633–645. 5 indexed citations
6.
Shuaibu, Aliyu Nuhu, et al.. (2017). Sparse Representation for Crowd Attributes Recognition. IEEE Access. 5. 10422–10433. 5 indexed citations
7.
Subhani, Ahmad Rauf, Nidal Kamel, Mohamad Naufal Mohamad Saad, et al.. (2017). Mitigation of stress: new treatment alternatives. Cognitive Neurodynamics. 12(1). 1–20. 43 indexed citations
8.
Jatoi, Munsif Ali, et al.. (2017). Framework for estimating active brain sources using MUSIC and Root MUSIC. 1–6. 2 indexed citations
9.
Mumtaz, Wajid, et al.. (2017). An EEG-based functional connectivity measure for automatic detection of alcohol use disorder. Artificial Intelligence in Medicine. 84. 79–89. 45 indexed citations
10.
Jatoi, Munsif Ali, Nidal Kamel, Aamir Saeed Malik, et al.. (2016). EEG‐based brain source localization using visual stimuli. International Journal of Imaging Systems and Technology. 26(1). 55–64. 10 indexed citations
11.
Amin, Hafeez Ullah, Aamir Saeed Malik, Nidal Kamel, & Muhammad Hussain. (2015). A Novel Approach Based on Data Redundancy for Feature Extraction of EEG Signals. Brain Topography. 29(2). 207–217. 30 indexed citations
12.
Malik, Aamir Saeed, et al.. (2015). Decoding of visual information from human brain activity: A review of fMRI and EEG studies. Journal of Integrative Neuroscience. 14(2). 155–168. 18 indexed citations
13.
Kamel, Nidal, et al.. (2014). EEG based driver cognitive distraction assessment. 1–4. 14 indexed citations
14.
Hani, Ahmad Fadzil M., et al.. (2013). Identification of noise in the fundus images. 191–196. 12 indexed citations
15.
Manzoor, S., Varun Jeoti, Nidal Kamel, & Muhammad Asif Khan. (2011). Novel SNR Estimation Teachnique In Wireless OFDM Systems. 4(4). 1–20. 1 indexed citations
16.
Kamel, Nidal, Md Shohel Sayeed, & Grant Ellis. (2008). Glove-Based Approach to Online Signature Verification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 30(6). 1109–1113. 66 indexed citations
17.
Kamel, Nidal & Mohd Zuki Yusoff. (2008). A generalized subspace approach for estimating visual evoked potentials. PubMed. 2008. 5208–5211. 4 indexed citations
18.
Kamel, Nidal & Varun Jeoti. (2007). A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel. ETRI Journal. 29(5). 607–613. 7 indexed citations
19.
Sim, K. S., Nidal Kamel, & H. T. Chuah. (2006). Autoregressive Wiener filtering in a scanning electron microscopy imaging system. Scanning. 27(3). 147–153. 8 indexed citations
20.
Sim, K. S. & Nidal Kamel. (2004). Image signal‐to‐noise ratio estimation using the autoregressive model. Scanning. 26(3). 135–139. 24 indexed citations

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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