Muhammad Ibrahim
Impact in
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- AI in cancer detection
- Sentiment Analysis and Opinion Mining
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- Digital Media Forensic Detection
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Sentiment Analysis and Opinion Mining 3
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- Generative Adversarial Networks and Image Synthesis 2
- Face recognition and analysis 2
- Digital Media Forensic Detection 2
- Co-authors
- Imran Sarwar Bajwa (7 shared papers)Nadeem Sarwar (4 shared papers)Shahzad Mumtaz (5 shared papers)Saeed Ahmad (3 shared papers)Muhammad Zunnurain Hussain (2 shared papers)Muhammad Tahir (1 shared paper)Muhammad Shafi (1 shared paper)Fahima Hajjej (1 shared paper)
- Journals
- IEEE Access (3 papers)Sustainability (1 paper)Scientific Reports (1 paper)SLAS TECHNOLOGY (1 paper)Computers, materials & continua/Computers, materials & continua (Print) (1 paper)
- Partner nations
- PakistanSaudi ArabiaSouth Korea
In The Last Decade
Muhammad Ibrahim
14 papers receiving 217 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 80
- Computer Vision and Pattern Recognition 49
- Information Systems 44
- Oncology 41
- Signal Processing 16
Countries citing papers authored by Muhammad Ibrahim
This map shows the geographic impact of Muhammad Ibrahim'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 Ibrahim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Ibrahim more than expected).
Fields of papers citing papers by Muhammad Ibrahim
This network shows the impact of papers produced by Muhammad Ibrahim. 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 Ibrahim. The network helps show where Muhammad Ibrahim may publish in the future.
Co-authors
The 25 scholars most cited alongside Muhammad Ibrahim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 49 | |
| 2 | 2023 | 35 | |
| 3 | 2023 | 29 | |
| 4 | 2024 | 22 | |
| 5 | 2022 | 21 | |
| 6 | 2019 | 17 | |
| 7 | 2023 | 13 | |
| 8 | 2022 | 12 | |
| 9 | 2018 | 9 | |
| 10 | 2024 | 6 | |
| 11 | 2016 | 5 | |
| 12 | 2022 | 4 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2023 | 0 | |
| 17 | 2025 | 0 |
About Muhammad Ibrahim
Muhammad Ibrahim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computational Theory and Mathematics and Computer Networks and Communications, having authored 17 papers that have together received 224 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Computational Drug Discovery Methods (2 papers), Face recognition and analysis (2 papers), Digital Media Forensic Detection (2 papers), Digital Marketing and Social Media (2 papers), Music and Audio Processing (2 papers) and Recommender Systems and Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (80 citations), Computer Vision and Pattern Recognition (49 citations), Information Systems (44 citations), Oncology (41 citations) and Signal Processing (16 citations). Muhammad Ibrahim has collaborated with scholars based in Pakistan, Saudi Arabia and South Korea. Frequent co-authors include Imran Sarwar Bajwa, Nadeem Sarwar, Shahzad Mumtaz, Saeed Ahmad, Muhammad Zunnurain Hussain, Muhammad Tahir, Muhammad Shafi, Fahima Hajjej, Muhammad Tanveer and Christine Dewi. Their work appears in journals such as IEEE Access, Sustainability, Scientific Reports, SLAS TECHNOLOGY and Computers, materials & continua/Computers, materials & continua (Print).
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.