Muhammad Islam

1.4k total citations
62 papers, 898 citations indexed

About

Muhammad Islam is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Muhammad Islam has authored 62 papers receiving a total of 898 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Electrical and Electronic Engineering, 16 papers in Computer Vision and Pattern Recognition and 15 papers in Artificial Intelligence. Recurrent topics in Muhammad Islam's work include Video Surveillance and Tracking Methods (8 papers), Smart Agriculture and AI (8 papers) and Anomaly Detection Techniques and Applications (7 papers). Muhammad Islam is often cited by papers focused on Video Surveillance and Tracking Methods (8 papers), Smart Agriculture and AI (8 papers) and Anomaly Detection Techniques and Applications (7 papers). Muhammad Islam collaborates with scholars based in Saudi Arabia, Pakistan and South Korea. Muhammad Islam's co-authors include Shabana Habib, Sheroz Khan, Waleed Albattah, Mohammed Aloraini, Mohammed F. Alsharekh, Suliman Aladhadh, Saleh Alyahya, Abdullah M. Alnajim, Taimoor Ashraf Khan and Deshinta Arrova Dewi and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Muhammad Islam

57 papers receiving 860 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 Islam Saudi Arabia 19 244 236 214 150 84 62 898
Shabana Habib Saudi Arabia 17 288 1.2× 287 1.2× 184 0.9× 183 1.2× 110 1.3× 53 873
Sandeep Kautish India 21 304 1.2× 163 0.7× 96 0.4× 236 1.6× 161 1.9× 64 906
Meshal Alharbi Saudi Arabia 17 186 0.8× 158 0.7× 126 0.6× 110 0.7× 67 0.8× 70 711
Muhammad Saleem Pakistan 15 245 1.0× 135 0.6× 117 0.5× 217 1.4× 208 2.5× 36 896
Avinash Sharma India 18 195 0.8× 151 0.6× 108 0.5× 206 1.4× 172 2.0× 113 964
Ahmad Ali AlZubi Saudi Arabia 18 214 0.9× 158 0.7× 186 0.9× 374 2.5× 250 3.0× 91 1.1k
Hani Alquhayz Saudi Arabia 17 318 1.3× 130 0.6× 141 0.7× 196 1.3× 107 1.3× 55 915
Ahmed A. Elngar Egypt 14 326 1.3× 215 0.9× 72 0.3× 119 0.8× 111 1.3× 84 855
Kamal Gulati India 12 178 0.7× 97 0.4× 133 0.6× 210 1.4× 97 1.2× 33 689

Countries citing papers authored by Muhammad Islam

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Islam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Islam

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Islam. A scholar is included among the top collaborators of Muhammad Islam 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 Islam. Muhammad Islam 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.
Bilal, Hazrat, Sushil Kumar Singh, Abdullah M. Alnajim, et al.. (2025). Optimized Attention Assisted Network for Forensic-Aware Malware Detection in Consumer Electronics. IEEE Transactions on Consumer Electronics. 71(4). 11113–11120.
2.
Khan, Habib Ullah, Zahoor Jan, Inam Ullah, et al.. (2024). A deep dive into AI integration and advanced nanobiosensor technologies for enhanced bacterial infection monitoring. Nanotechnology Reviews. 13(1). 26 indexed citations
3.
Singh, Sushil Kumar, et al.. (2024). Optimizing healthcare data quality with optimal features driven mutual entropy gain. Expert Systems. 42(2). 1 indexed citations
4.
Islam, Muhammad, et al.. (2024). Optimal Features Driven Attention Network With Medium-Scale Benchmark for Wheat Diseases Recognition. IEEE Access. 12. 150739–150753. 1 indexed citations
5.
Habib, Shabana, et al.. (2024). Effective Video Summarization Using Channel Attention-Assisted Encoder–Decoder Framework. Symmetry. 16(6). 680–680. 3 indexed citations
6.
Ullah, Inam, et al.. (2024). A comprehensive systematic literature review of ML in nanotechnology for sustainable development. Nanotechnology Reviews. 13(1). 12 indexed citations
7.
Singh, Sushil Kumar, et al.. (2024). Multiscale attention-over-attention network for retinal disease recognition in OCT radiology images. Frontiers in Medicine. 11. 1499393–1499393. 1 indexed citations
8.
Aloraini, Mohammed, et al.. (2023). Wind Energy Assessment Using Weibull Distribution with Different Numerical Estimation Methods: A Case Study. Emerging Science Journal. 7(6). 2260–2278. 27 indexed citations
9.
Alnajim, Abdullah M., et al.. (2023). Mitigating the Risks of Malware Attacks with Deep Learning Techniques. Electronics. 12(14). 3166–3166. 8 indexed citations
10.
Habib, Shabana, et al.. (2023). Computer Network Redundancy Reduction Using Video Compression. Symmetry. 15(6). 1280–1280. 1 indexed citations
11.
Islam, Muhammad, et al.. (2023). Enhancing Short-Term Electrical Load Forecasting for Sustainable Energy Management in Low-Carbon Buildings. Sustainability. 15(24). 16885–16885. 8 indexed citations
12.
Aloraini, Mohammed, et al.. (2023). Combining the Transformer and Convolution for Effective Brain Tumor Classification Using MRI Images. Applied Sciences. 13(6). 3680–3680. 45 indexed citations
13.
Islam, Muhammad, Mohammed Aloraini, Suliman Aladhadh, et al.. (2023). Toward a Vision-Based Intelligent System: A Stacked Encoded Deep Learning Framework for Sign Language Recognition. Sensors. 23(22). 9068–9068. 11 indexed citations
14.
Islam, Muhammad, et al.. (2023). An IoT Enable Anomaly Detection System for Smart City Surveillance. Sensors. 23(4). 2358–2358. 27 indexed citations
15.
Habib, Shabana, et al.. (2023). Solar Power Prediction Using Dual Stream CNN-LSTM Architecture. Sensors. 23(2). 945–945. 44 indexed citations
16.
Habib, Shabana, et al.. (2022). A Deep-Learning Model for Real-Time Red Palm Weevil Detection and Localization. Journal of Imaging. 8(6). 170–170. 16 indexed citations
17.
Farman, Haleem, Taimoor Ashraf Khan, Zahid Khan, et al.. (2022). Real-Time Face Mask Detection to Ensure COVID-19 Precautionary Measures in the Developing Countries. Applied Sciences. 12(8). 3879–3879. 16 indexed citations
18.
Alsharekh, Mohammed F., Shabana Habib, Deshinta Arrova Dewi, et al.. (2022). Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM. Sensors. 22(18). 6913–6913. 48 indexed citations
19.
Albattah, Waleed, Shabana Habib, Mohammed F. Alsharekh, et al.. (2022). An Overview of the Current Challenges, Trends, and Protocols in the Field of Vehicular Communication. Electronics. 11(21). 3581–3581. 25 indexed citations
20.
Aladhadh, Suliman, et al.. (2022). An Effective Skin Cancer Classification Mechanism via Medical Vision Transformer. Sensors. 22(11). 4008–4008. 66 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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