Mahmoud Khademi
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Materials Chemistry
- Co-authors
- Dominik P. J. BarzOliver SchulteNedialko S. NedialkovAsghar Molaei DehkordiMohammad Taghi ManzuriMehrsan JavanLouis–Philippe MorencySaeed Zeinali Heris
- Topics
- Advanced Image and Video Retrieval Techniques (4 papers)Multimodal Machine Learning Applications (4 papers)Human Pose and Action Recognition (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaLangmuirMicroporous and Mesoporous Materials
- Partner nations
- CanadaIranUnited States
In The Last Decade
Mahmoud Khademi
17 papers receiving 367 citations
Peers
Comparison fields: 5 of 83
- Biomedical Engineering 91
- Computer Vision and Pattern Recognition 79
- Artificial Intelligence 71
- Electrical and Electronic Engineering 68
- Materials Chemistry 55
Countries citing papers authored by Mahmoud Khademi
This map shows the geographic impact of Mahmoud Khademi'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 Mahmoud Khademi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahmoud Khademi more than expected).
Fields of papers citing papers by Mahmoud Khademi
This network shows the impact of papers produced by Mahmoud Khademi. 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 Mahmoud Khademi. The network helps show where Mahmoud Khademi may publish in the future.
Co-authorship network of co-authors of Mahmoud Khademi
This figure shows the co-authorship network connecting the top 25 collaborators of Mahmoud Khademi. A scholar is included among the top collaborators of Mahmoud Khademi 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 Mahmoud Khademi. Mahmoud Khademi 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 | 2 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 20 | |
| 8 | 25 | |
| 9 | 108 | |
| 10 | 11 | |
| 11 | 4 | |
| 12 | 16 | |
| 13 | 22 | |
| 14 | 68 | |
| 15 | 6 | |
| 16 | 39 | |
| 17 | 8 | |
| 18 | 23 | |
| 19 | 14 |
About Mahmoud Khademi
Mahmoud Khademi is a scholar working on Computer Vision and Pattern Recognition, Bioengineering and Physical and Theoretical Chemistry, having authored 19 papers that have together received 375 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Bioengineering (26 citations), Computer Vision and Pattern Recognition (79 citations) and Electrochemistry (23 citations). Mahmoud Khademi has collaborated with scholars based in Canada, Iran and United States. Frequent co-authors include Dominik P. J. Barz, Oliver Schulte, Nedialko S. Nedialkov, Asghar Molaei Dehkordi, Mohammad Taghi Manzuri, Mehrsan Javan, Louis–Philippe Morency, Saeed Zeinali Heris, Ziyi Yang and Yang Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, Langmuir and Microporous and Mesoporous Materials.
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.