Muhammad Fahim
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Co-authors
- Alberto SillittiIram FatimaYoung-Koo LeeThar BakerSungyoung LeeTrung Q. DuongVishal SharmaMohammed Al-Khafajiy
- Topics
- Context-Aware Activity Recognition Systems (17 papers)IoT and Edge/Fog Computing (7 papers)Anomaly Detection Techniques and Applications (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Networks and CommunicationsSignal Processing
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessIEEE Communications Magazine
- Partner nations
- PakistanUnited KingdomSouth Korea
In The Last Decade
Muhammad Fahim
67 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 134
- Computer Networks and Communications 335
- Artificial Intelligence 312
- Computer Vision and Pattern Recognition 303
- Electrical and Electronic Engineering 273
- Biomedical Engineering 152
Countries citing papers authored by Muhammad Fahim
This map shows the geographic impact of Muhammad Fahim'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 Fahim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Fahim more than expected).
Fields of papers citing papers by Muhammad Fahim
This network shows the impact of papers produced by Muhammad Fahim. 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 Fahim. The network helps show where Muhammad Fahim may publish in the future.
Co-authorship network of co-authors of Muhammad Fahim
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Fahim. A scholar is included among the top collaborators of Muhammad Fahim 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 Fahim. Muhammad Fahim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 11 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 10 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | 0 | |
| 16 | 0 | |
| 17 | 2 | |
| 18 | Identification of stressors and Perceptional difference of stress in first and final year Doctor of Physical Therapy students; a comparative study. | 10 |
| 19 | 6 | |
| 20 | 2 |
About Muhammad Fahim
Muhammad Fahim is a scholar working on General Dentistry, Computer Vision and Pattern Recognition and Issues, ethics and legal aspects, having authored 77 papers that have together received 1.2k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (17 papers), IoT and Edge/Fog Computing (7 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (303 citations), Computer Networks and Communications (335 citations) and Signal Processing (105 citations). Muhammad Fahim has collaborated with scholars based in Pakistan, United Kingdom and South Korea. Frequent co-authors include Alberto Sillitti, Iram Fatima, Young-Koo Lee, Thar Baker, Sungyoung Lee, Trung Q. Duong, Vishal Sharma, Mohammed Al-Khafajiy, Carl Chalmers and Hoshang Kolivand. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Communications Magazine.
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.