Manar D. Samad
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Cardiology and Cardiovascular Medicine
- Electrical and Electronic Engineering
- Co-authors
- Khan M. IftekharuddinNorou DiawaraBrandon K. FornwaltChristopher M. HaggertyLinyuan JingGregory J WehnerJonna BobzienJohn W. Harrington
- Topics
- Domain Adaptation and Few-Shot Learning (6 papers)graph theory and CDMA systems (6 papers)Face recognition and analysis (5 papers)
- Partner nations
- United StatesMalaysiaBangladesh
In The Last Decade
Manar D. Samad
42 papers receiving 511 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 208
- Radiology, Nuclear Medicine and Imaging 82
- Computer Vision and Pattern Recognition 78
- Cardiology and Cardiovascular Medicine 77
- Electrical and Electronic Engineering 76
Countries citing papers authored by Manar D. Samad
This map shows the geographic impact of Manar D. Samad'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 Manar D. Samad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manar D. Samad more than expected).
Fields of papers citing papers by Manar D. Samad
This network shows the impact of papers produced by Manar D. Samad. 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 Manar D. Samad. The network helps show where Manar D. Samad may publish in the future.
Co-authorship network of co-authors of Manar D. Samad
This figure shows the co-authorship network connecting the top 25 collaborators of Manar D. Samad. A scholar is included among the top collaborators of Manar D. Samad 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 Manar D. Samad. Manar D. Samad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 34 | |
| 6 | 6 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 47 | |
| 10 | 8 | |
| 11 | 7 | |
| 12 | 1 | |
| 13 | 7 | |
| 14 | 6 | |
| 15 | 111 | |
| 16 | 47 | |
| 17 | 13 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | 40 |
About Manar D. Samad
Manar D. Samad is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 48 papers that have together received 534 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), graph theory and CDMA systems (6 papers) and Face recognition and analysis (5 papers). The work is most often cited by research in Health Informatics (26 citations), Health Information Management (53 citations) and Artificial Intelligence (208 citations). Manar D. Samad has collaborated with scholars based in United States, Malaysia and Bangladesh. Frequent co-authors include Khan M. Iftekharuddin, Norou Diawara, Brandon K. Fornwalt, Christopher M. Haggerty, Linyuan Jing, Gregory J Wehner, Jonna Bobzien, John W. Harrington, Brent A. Williams and Alvaro Ulloa. Their work appears in journals such as Neurocomputing, Neural Networks and Knowledge-Based Systems.
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.