Payman Moallem

4.2k total citations
112 papers, 1.6k citations indexed

About

Payman Moallem is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Media Technology. According to data from OpenAlex, Payman Moallem has authored 112 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Computer Vision and Pattern Recognition, 24 papers in Electrical and Electronic Engineering and 21 papers in Media Technology. Recurrent topics in Payman Moallem's work include Advanced Vision and Imaging (20 papers), Advanced Image and Video Retrieval Techniques (13 papers) and Image Processing Techniques and Applications (11 papers). Payman Moallem is often cited by papers focused on Advanced Vision and Imaging (20 papers), Advanced Image and Video Retrieval Techniques (13 papers) and Image Processing Techniques and Applications (11 papers). Payman Moallem collaborates with scholars based in Iran, India and Malaysia. Payman Moallem's co-authors include Saed Moradi, Arash Kiyoumarsi, Mohamad Farzan Sabahi, Behzad Mirzaeian Dehkordi, Mohammad Hossein Vafaie, Navid Razmjooy, Hossein Pourghassem, Mehdi Momeni, S. Amirhassan Monadjemi and Karim Faez and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Industrial Electronics and IEEE Transactions on Power Electronics.

In The Last Decade

Payman Moallem

107 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Payman Moallem Iran 20 548 455 285 258 218 112 1.6k
Qingqing Dang China 9 142 0.3× 700 1.5× 381 1.3× 158 0.6× 133 0.6× 25 1.6k
S. N. Merchant India 20 581 1.1× 441 1.0× 231 0.8× 274 1.1× 178 0.8× 204 1.7k
P. Rajalakshmi India 18 478 0.9× 194 0.4× 113 0.4× 64 0.2× 136 0.6× 204 1.4k
Zhen Jia China 9 128 0.2× 820 1.8× 215 0.8× 140 0.5× 200 0.9× 22 1.4k
Mengchen Liu United Kingdom 6 152 0.3× 1.3k 2.8× 220 0.8× 301 1.2× 438 2.0× 7 1.9k
Akif Durdu Türkiye 20 206 0.4× 417 0.9× 304 1.1× 32 0.1× 358 1.6× 92 1.4k
P. Palanisamy India 23 179 0.3× 636 1.4× 174 0.6× 194 0.8× 269 1.2× 144 1.9k
Ángel D. Sappa Spain 26 144 0.3× 1.9k 4.3× 698 2.4× 512 2.0× 182 0.8× 154 2.7k
Xuran Pan China 11 128 0.2× 989 2.2× 256 0.9× 313 1.2× 331 1.5× 16 1.7k

Countries citing papers authored by Payman Moallem

Since Specialization
Citations

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

Fields of papers citing papers by Payman Moallem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Payman Moallem

This figure shows the co-authorship network connecting the top 25 collaborators of Payman Moallem. A scholar is included among the top collaborators of Payman Moallem 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 Payman Moallem. Payman Moallem 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.
Moallem, Payman, et al.. (2025). High performance frame selection algorithm for gray-level frames within the framework of multi-frame super-resolution. Digital Signal Processing. 164. 105217–105217.
2.
Kazemi, Mohammad, et al.. (2024). Video anomaly detection using transformers and ensemble of convolutional auto-encoders. Computers & Electrical Engineering. 120. 109879–109879. 2 indexed citations
3.
Kazemi, Mohammad, et al.. (2024). Video anomaly detection based on attention and efficient spatio-temporal feature extraction. The Visual Computer. 40(10). 6825–6841. 4 indexed citations
4.
Momeni, Mehdi, et al.. (2023). A fusion-based approach to improve hyperspectral images’ classification using metaheuristic band selection. Applied Soft Computing. 148. 110753–110753. 4 indexed citations
5.
Moallem, Payman, et al.. (2023). A High-Sensitive Fiber Specklegram Refractive Index Sensor With Microfiber Adjustable Sensing Area. IEEE Sensors Journal. 23(14). 15570–15577. 14 indexed citations
6.
Moallem, Payman, et al.. (2023). Multi-stage morphological operators for small infrared target detection. Optik. 276. 170597–170597. 2 indexed citations
7.
Momeni, Mehdi, et al.. (2022). Semisupervised Band Selection From Hyperspectral Images Using Levy Flight-Based Genetic Algorithm. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 19 indexed citations
8.
9.
Moallem, Payman, et al.. (2022). Depth Map Super Resolution Using Structure-Preserving Guided Filtering. IEEE Sensors Journal. 22(13). 13144–13152. 3 indexed citations
10.
Moallem, Payman, et al.. (2022). Large scaling factor depth map super-resolution using progressive joint-multilateral filtering. Multimedia Tools and Applications. 81(8). 11461–11478.
11.
Moallem, Payman, et al.. (2020). Statistical Based Algorithm for Reducing Residual Error in Embedded Systems Implemented Using the Controller Area Network. IEEE Access. 8. 133817–133826. 1 indexed citations
12.
Moallem, Payman, et al.. (2019). Decision fusion using virtual dictionary‐based sparse representation for robust SAR automatic target recognition. IET Radar Sonar & Navigation. 14(6). 811–821. 2 indexed citations
13.
Moallem, Payman, et al.. (2019). An interpolation filter based on natural neighbor Galerkin method for salt and pepper noise restoration with adaptive size local filtering window. Signal Image and Video Processing. 13(5). 895–903. 3 indexed citations
14.
Memarmoghadam, Alireza & Payman Moallem. (2019). Size-aware visual object tracking via dynamic fusion of correlation filter-based part regressors. Signal Processing. 164. 84–98. 3 indexed citations
15.
Momeni, Mehdi, et al.. (2019). Transferable Object-Based Framework Based on Deep Convolutional Neural Networks for Building Extraction. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(8). 2627–2635. 25 indexed citations
16.
Moradi, Saed, Payman Moallem, & Mohamad Farzan Sabahi. (2018). Fast and Robust Small Infrared Target Detection Using Absolute Directional Mean Difference Algorithm. arXiv (Cornell University). 135 indexed citations
17.
Moallem, Payman, et al.. (2018). A structural refinement method based on image gradient for improving performance of noise-restoration stage in decision based filters. Digital Signal Processing. 75. 242–254. 1 indexed citations
18.
Moallem, Payman, et al.. (2018). Structure‐based interpolation method for restoring the intensity of low‐density impulse noise. IET Image Processing. 12(9). 1577–1585. 1 indexed citations
19.
Moallem, Payman, et al.. (2018). Using Kalman filter in the frequency domain for multi-frame scalable super resolution. Signal Processing. 155. 108–129. 6 indexed citations
20.
Moallem, Payman, et al.. (2018). A structural post-processing method for enhancing intensity restoration of low-density impulse-noise for decision based filters. Journal of Visual Communication and Image Representation. 51. 40–55. 1 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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