Majid Komeili

631 total citations
33 papers, 432 citations indexed

About

Majid Komeili is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Majid Komeili has authored 33 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 9 papers in Cognitive Neuroscience and 9 papers in Artificial Intelligence. Recurrent topics in Majid Komeili's work include EEG and Brain-Computer Interfaces (9 papers), ECG Monitoring and Analysis (7 papers) and Video Surveillance and Tracking Methods (6 papers). Majid Komeili is often cited by papers focused on EEG and Brain-Computer Interfaces (9 papers), ECG Monitoring and Analysis (7 papers) and Video Surveillance and Tracking Methods (6 papers). Majid Komeili collaborates with scholars based in Canada, Iran and United States. Majid Komeili's co-authors include Narges Armanfard, Dimitrios Hatzinakos, J.P. Reilly, Ehsanollah Kabir, Morteza Valizadeh, John F. Connolly, Kathleen Fraser, Chloé Pou-Prom, Frank Rudzicz and Saeed Jalili and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Majid Komeili

33 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Majid Komeili Canada 11 167 122 107 107 85 33 432
Kiran Kumar Patro India 14 124 0.7× 144 1.2× 165 1.5× 102 1.0× 55 0.6× 24 502
Allam Jaya Prakash India 15 160 1.0× 162 1.3× 177 1.7× 115 1.1× 43 0.5× 30 633
Alaa Eleyan Türkiye 12 366 2.2× 50 0.4× 54 0.5× 88 0.8× 95 1.1× 56 595
Ayman Ibaida Australia 10 207 1.2× 54 0.4× 158 1.5× 69 0.6× 92 1.1× 22 457
Sang‐Woong Lee South Korea 10 212 1.3× 69 0.6× 55 0.5× 232 2.2× 37 0.4× 19 519
Seral Özşen Türkiye 11 51 0.3× 169 1.4× 73 0.7× 108 1.0× 50 0.6× 38 453
U. C. Niranjan India 11 275 1.6× 113 0.9× 103 1.0× 39 0.4× 71 0.8× 28 474
Sajid Gul Khawaja Pakistan 12 95 0.6× 113 0.9× 60 0.6× 65 0.6× 54 0.6× 50 496
Vijay Kumar Bohat India 11 112 0.7× 88 0.7× 92 0.9× 98 0.9× 20 0.2× 18 422
K.L. Chan Hong Kong 9 335 2.0× 65 0.5× 106 1.0× 70 0.7× 89 1.0× 16 560

Countries citing papers authored by Majid Komeili

Since Specialization
Citations

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

Fields of papers citing papers by Majid Komeili

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Majid Komeili

This figure shows the co-authorship network connecting the top 25 collaborators of Majid Komeili. A scholar is included among the top collaborators of Majid Komeili 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 Majid Komeili. Majid Komeili 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.
Kim, Anne, et al.. (2025). Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review. British Journal of Anaesthesia. 135(3). 561–570. 1 indexed citations
2.
Komeili, Majid, et al.. (2024). Interpretable few-shot learning with online attribute selection. Neurocomputing. 614. 128755–128755. 2 indexed citations
3.
Amirani, Mehdi Chehel, et al.. (2024). Pseudo-class part prototype networks for interpretable breast cancer classification. Scientific Reports. 14(1). 10341–10341. 3 indexed citations
4.
Komeili, Majid, et al.. (2023). On the interpretability of part-prototype based classifiers: a human centric analysis. Scientific Reports. 13(1). 23088–23088. 3 indexed citations
5.
Fraser, Kathleen, et al.. (2023). Reference-Free Summarization Evaluation with Large Language Models. 1 indexed citations
6.
Komeili, Majid, et al.. (2022). Predictive modelling of Parkinson’s disease progression based on RNA-Sequence with densely connected deep recurrent neural networks. Scientific Reports. 12(1). 21469–21469. 2 indexed citations
7.
Komeili, Majid, et al.. (2021). Cause and Effect: Concept-based Explanation of Neural Networks. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2730–2736. 3 indexed citations
8.
Komeili, Majid, Narges Armanfard, & Dimitrios Hatzinakos. (2020). Multiview Feature Selection for Single-View Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(10). 3573–3586. 25 indexed citations
9.
Komeili, Majid, et al.. (2019). Talk2Me: Automated linguistic data collection for personal assessment. PLoS ONE. 14(3). e0212342–e0212342. 14 indexed citations
10.
Armanfard, Narges, Majid Komeili, J.P. Reilly, & John F. Connolly. (2018). A Machine Learning Framework for Automatic and Continuous MMN Detection With Preliminary Results for Coma Outcome Prediction. IEEE Journal of Biomedical and Health Informatics. 23(4). 1794–1804. 19 indexed citations
11.
Komeili, Majid, Narges Armanfard, & Dimitrios Hatzinakos. (2018). Liveness Detection and Automatic Template Updating Using Fusion of ECG and Fingerprint. IEEE Transactions on Information Forensics and Security. 13(7). 1810–1822. 44 indexed citations
12.
Armanfard, Narges, J.P. Reilly, & Majid Komeili. (2017). Logistic Localized Modeling of the Sample Space for Feature Selection and Classification. IEEE Transactions on Neural Networks and Learning Systems. 29(5). 1396–1413. 17 indexed citations
13.
Armanfard, Narges, et al.. (2016). Automatic and continuous assessment of ERPs for mismatch negativity detection. PubMed. 32. 969–972. 2 indexed citations
14.
Komeili, Majid, et al.. (2016). On evaluating human recognition using electrocardiogram signals: From rest to exercise. 1–4. 7 indexed citations
15.
Armanfard, Narges, et al.. (2016). Vigilance lapse identification using sparse EEG electrode arrays. 1–4. 8 indexed citations
16.
Armanfard, Narges, et al.. (2009). A non-parametric pixel-based background modeling for dynamic scenes. 40. 369–373. 9 indexed citations
17.
Valizadeh, Morteza, Narges Armanfard, Majid Komeili, & Ehsanollah Kabir. (2009). A novel hybrid algorithm for binarization of badly illuminated document images. 121–126. 19 indexed citations
18.
Armanfard, Narges, Morteza Valizadeh, Majid Komeili, & Ehsanollah Kabir. (2009). Document image binarization by using texture-edge descriptor. 134–139. 2 indexed citations
19.
Komeili, Majid, Morteza Valizadeh, Narges Armanfard, & Ehsanollah Kabir. (2009). An optimal fuzzy system for feature reliability measuring in particle filter-based object tracking. 25. 47–53. 1 indexed citations
20.
Komeili, Majid, Narges Armanfard, & Ehsanollah Kabir. (2008). A fuzzy approach for multi-feature pedestrian tracking with particle filter. 58. 570–575. 4 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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