Akmal A. Younis
- Computer Vision and Pattern Recognition top 10%
- Neurology top 10%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging
- Cellular and Molecular Neuroscience
- Co-authors
- Mansur R. KabukaNigel JohnPradip M. PattanyMohamed IbrahimJames B. MurdochRobert DuncanFrancisco Tellechea RottaRobert M. Quencer
- Topics
- Medical Image Segmentation Techniques (6 papers)Advanced Image and Video Retrieval Techniques (4 papers)Gene expression and cancer classification (3 papers)
- Journals
- BMC GenomicsIEEE Transactions on Circuits and Systems for Video TechnologyImage and Vision Computing
- Partner nations
- United StatesEgyptUnited Arab Emirates
In The Last Decade
Akmal A. Younis
19 papers receiving 316 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 124
- Neurology 101
- Molecular Biology 57
- Radiology, Nuclear Medicine and Imaging 53
- Cellular and Molecular Neuroscience 51
Countries citing papers authored by Akmal A. Younis
This map shows the geographic impact of Akmal A. Younis'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 Akmal A. Younis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akmal A. Younis more than expected).
Fields of papers citing papers by Akmal A. Younis
This network shows the impact of papers produced by Akmal A. Younis. 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 Akmal A. Younis. The network helps show where Akmal A. Younis may publish in the future.
Co-authorship network of co-authors of Akmal A. Younis
This figure shows the co-authorship network connecting the top 25 collaborators of Akmal A. Younis. A scholar is included among the top collaborators of Akmal A. Younis 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 Akmal A. Younis. Akmal A. Younis 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 | 14 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 19 | |
| 7 | 20 | |
| 8 | 2 | |
| 9 | 17 | |
| 10 | 3 | |
| 11 | 8 | |
| 12 | 3 | |
| 13 | 47 | |
| 14 | Innovative grid technologies applied to bioinformatics and hurricane mitigation | 7 |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 35 | |
| 18 | MR imaging and localized proton spectroscopy of the precentral gyrus in amyotrophic lateral sclerosis. | 120 |
| 19 | 1 | |
| 20 | 13 |
About Akmal A. Younis
Akmal A. Younis is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Information Systems and Management, having authored 20 papers that have together received 329 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in Neurology (101 citations), Computer Vision and Pattern Recognition (124 citations) and Neurology (43 citations). Akmal A. Younis has collaborated with scholars based in United States, Egypt and United Arab Emirates. Frequent co-authors include Mansur R. Kabuka, Nigel John, Pradip M. Pattany, Mohamed Ibrahim, James B. Murdoch, Robert Duncan, Francisco Tellechea Rotta, Robert M. Quencer, Walter G. Bradley and Brian C. Bowen. Their work appears in journals such as BMC Genomics, IEEE Transactions on Circuits and Systems for Video Technology and Image and Vision Computing.
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.