Muhammad Ali Qureshi

1.9k total citations
98 papers, 1.2k citations indexed

About

Muhammad Ali Qureshi is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Muhammad Ali Qureshi has authored 98 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computer Vision and Pattern Recognition, 27 papers in Electrical and Electronic Engineering and 10 papers in Aerospace Engineering. Recurrent topics in Muhammad Ali Qureshi's work include Image and Video Quality Assessment (11 papers), Image Enhancement Techniques (10 papers) and Digital Media Forensic Detection (9 papers). Muhammad Ali Qureshi is often cited by papers focused on Image and Video Quality Assessment (11 papers), Image Enhancement Techniques (10 papers) and Digital Media Forensic Detection (9 papers). Muhammad Ali Qureshi collaborates with scholars based in Pakistan, Saudi Arabia and France. Muhammad Ali Qureshi's co-authors include Mohamed Deriche, Azeddine Beghdadi, Muhammad Amjad, El-Sayed M. El-Alfy, Muhammad Zahid Latif, Asjad Amin, Ashiq Hussain, Najeeb Alam Khan, Muhammad Omer Khan and Abdul Aziz and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Energies.

In The Last Decade

Muhammad Ali Qureshi

88 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Ali Qureshi Pakistan 18 522 248 177 131 92 98 1.2k
M. M. Kamruzzaman Saudi Arabia 22 191 0.4× 357 1.4× 99 0.6× 98 0.7× 276 3.0× 87 1.6k
Rehan Ullah Khan Saudi Arabia 21 220 0.4× 143 0.6× 105 0.6× 114 0.9× 164 1.8× 85 1.1k
Surbhi Gupta India 14 293 0.6× 78 0.3× 43 0.2× 54 0.4× 135 1.5× 39 750
Hezerul Abdul Karim Malaysia 15 391 0.7× 72 0.3× 36 0.2× 27 0.2× 169 1.8× 110 849
Ming‐Ching Chang United States 20 1.3k 2.4× 73 0.3× 51 0.3× 11 0.1× 510 5.5× 108 1.7k
Hui Zeng China 15 360 0.7× 220 0.9× 65 0.4× 15 0.1× 74 0.8× 119 874
Sudeep D. Thepade India 18 1.4k 2.6× 31 0.1× 404 2.3× 50 0.4× 254 2.8× 258 1.9k
Rahul Chauhan India 10 189 0.4× 76 0.3× 36 0.2× 90 0.7× 186 2.0× 229 767
Jaeyoung Choi South Korea 14 254 0.5× 238 1.0× 80 0.5× 15 0.1× 195 2.1× 102 956
Mohsen Ebrahimi Moghaddam Iran 21 940 1.8× 63 0.3× 392 2.2× 7 0.1× 205 2.2× 107 1.4k

Countries citing papers authored by Muhammad Ali Qureshi

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Ali Qureshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Ali Qureshi. 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 Muhammad Ali Qureshi. The network helps show where Muhammad Ali Qureshi may publish in the future.

Co-authorship network of co-authors of Muhammad Ali Qureshi

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Ali Qureshi. A scholar is included among the top collaborators of Muhammad Ali Qureshi 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 Muhammad Ali Qureshi. Muhammad Ali Qureshi 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.
Qureshi, Muhammad Ali, et al.. (2024). A Comprehensive Review of Forensic Phonetics Techniques. 4(2).
2.
Amjad, Muhammad, et al.. (2024). Optimal PMU Placement to Enhance Observability in Transmission Networks Using ILP and Degree of Centrality. Energies. 17(9). 2140–2140. 9 indexed citations
3.
Qureshi, Muhammad Ali, et al.. (2024). Identification of true speakers from disguised voices in anti-forensic scenarios using an efficient framework. Signal Image and Video Processing. 18(10). 7455–7471. 1 indexed citations
4.
Amjad, Muhammad, et al.. (2023). Fast Convergence of Lightweight Deep Learning Models for Plant Leaf Disease Recognition. 1–5. 1 indexed citations
5.
Fátima, María de, et al.. (2023). From Microbes to Immunity: A Comprehensive Review of Microbiome Modulation. Journal of Health and Rehabilitation Research. 3(2). 801–807. 3 indexed citations
6.
Tariq, Sana, et al.. (2023). Towards the design of new cryptographic algorithm and performance evaluation measures. Multimedia Tools and Applications. 83(4). 9709–9759. 3 indexed citations
7.
Khan, Najeeb Alam, Muhammad Ali Qureshi, Saeed Akbar, & Asmat Ara. (2022). From chaos to encryption using fractional order Lorenz-Stenflo model with flux-controlled feedback memristor. Physica Scripta. 98(1). 14002–14002. 15 indexed citations
8.
Amjad, Muhammad, et al.. (2022). Handling Severity Levels of Multiple Co-Occurring Cotton Plant Diseases Using Improved YOLOX Model. IEEE Access. 10. 134811–134825. 37 indexed citations
9.
Qureshi, Muhammad Ali, et al.. (2022). An introduction to the parabolic equation method for electromagnetic wave propagation in tunnels. COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering. 41(5). 1313–1331. 1 indexed citations
10.
Amjad, Muhammad, et al.. (2021). Computationally light deep learning framework to recognize cotton leaf diseases. Journal of Intelligent & Fuzzy Systems. 40(6). 12383–12398. 17 indexed citations
11.
Khan, Najeeb Alam, et al.. (2020). Behavioral effects of a four-wing attractor with circuit realization: a cryptographic perspective on immersion. Communications in Theoretical Physics. 72(12). 125004–125004. 8 indexed citations
12.
Qureshi, Muhammad Ali, et al.. (2020). Smart Multiple Attendance System through Single Image. 1–5. 6 indexed citations
13.
Amin, Asjad, et al.. (2019). New attributes for salt dome detection in 3D seismic data using higher order SVD. Journal of Applied Geophysics. 163. 108–116. 4 indexed citations
14.
Beghdadi, Azeddine, et al.. (2018). Towards the design of smart video-surveillance system. Qatar University QSpace (Qatar University). 162–167. 9 indexed citations
15.
Qureshi, Muhammad Ali, Mohamed Deriche, Azeddine Beghdadi, & Asjad Amin. (2017). A critical survey of state-of-the-art image inpainting quality assessment metrics. Journal of Visual Communication and Image Representation. 49. 177–191. 47 indexed citations
16.
Qureshi, Muhammad Ali. (2017). Contrast Enhancement Evaluation Database (CEED2016). Data Archiving and Networked Services (DANS). 1. 9 indexed citations
17.
Qureshi, Muhammad Ali, Carsten H. Schmidt, & Thomas F. Eibert. (2012). Probe Pattern Inaccuracy in Multilevel Plane Wave Based Near-Field Far-Field Transformed Planar Near-Field Measurements. International Symposium on Antennas and Propagation. 1 indexed citations
18.
Qureshi, Muhammad Ali, et al.. (2010). Risk Factors for Kernicterus in Neonatal Jaundice. SHILAP Revista de lepidopterología. 8(1). 11 indexed citations
19.
Qureshi, Muhammad Ali, et al.. (2009). Co-inoculation with Mesorhizobium ciceri and Azotobacter chroococcum for improving growth, nodulation and yield of chickpea (Cicer arietinum L.). SHILAP Revista de lepidopterología. 15 indexed citations
20.
Qureshi, Muhammad Ali, et al.. (2009). Frequency of Depression in Migraine Patients. SHILAP Revista de lepidopterología.

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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