Mohammed A.‐M. Salem
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Cognitive Neuroscience
- Co-authors
- Mohamed RoushdySultan AlmotairiM. Abdel-AzizMohamed F. TolbaBadr AlmutairiAlaa KhamisFarid MelganiNilanjan Dey
- Topics
- Video Surveillance and Tracking Methods (20 papers)AI in cancer detection (14 papers)Advanced Neural Network Applications (11 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
In The Last Decade
Mohammed A.‐M. Salem
85 papers receiving 794 citations
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 352
- Artificial Intelligence 257
- Radiology, Nuclear Medicine and Imaging 239
- Pulmonary and Respiratory Medicine 105
- Cognitive Neuroscience 84
Countries citing papers authored by Mohammed A.‐M. Salem
This map shows the geographic impact of Mohammed A.‐M. Salem'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 Mohammed A.‐M. Salem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed A.‐M. Salem more than expected).
Fields of papers citing papers by Mohammed A.‐M. Salem
This network shows the impact of papers produced by Mohammed A.‐M. Salem. 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 Mohammed A.‐M. Salem. The network helps show where Mohammed A.‐M. Salem may publish in the future.
Co-authorship network of co-authors of Mohammed A.‐M. Salem
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed A.‐M. Salem. A scholar is included among the top collaborators of Mohammed A.‐M. Salem 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 Mohammed A.‐M. Salem. Mohammed A.‐M. Salem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 31 | |
| 8 | 11 | |
| 9 | 3 | |
| 10 | 8 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 1 | |
| 15 | 0 | |
| 16 | 5 | |
| 17 | 62 | |
| 18 | 8 | |
| 19 | MR-Brain Image Segmentation Using Gaussian Multiresolution Analysis and the EM Algorithm. | 23 |
| 20 | INVESTIGATION OF NOISE CHARCTRISTICS OF TANK CARRIERS: TITAN & KYNUS | 1 |
About Mohammed A.‐M. Salem
Mohammed A.‐M. Salem is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 99 papers that have together received 837 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (20 papers), AI in cancer detection (14 papers) and Advanced Neural Network Applications (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (352 citations), Radiology, Nuclear Medicine and Imaging (239 citations) and Neurology (84 citations). Mohammed A.‐M. Salem has collaborated with scholars based in Egypt, Germany and India. Frequent co-authors include Mohamed Roushdy, Sultan Almotairi, M. Abdel-Aziz, Mohamed F. Tolba, Badr Almutairi, Alaa Khamis, Farid Melgani, Nilanjan Dey, Beate Meffert and Mohamed A. Abd El Ghany. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.