Adil Khan
- Computer Vision and Pattern Recognition top 0.5%
- Media Technology top 0.5%
- Artificial Intelligence top 2%
- Biomedical Engineering top 5%
- Computer Networks and Communications top 5%
- Co-authors
- Muhammad AhmadYoung-Koo LeeManuel MazzaraSalvatore DistefanoTae‐Seong KimSungyoung LeeT.-S. KimMuhammad Hameed Siddiqi
- Topics
- Remote-Sensing Image Classification (23 papers)Context-Aware Activity Recognition Systems (19 papers)Face and Expression Recognition (11 papers)
- Partner nations
- RussiaSouth KoreaUnited Kingdom
In The Last Decade
Adil Khan
91 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Computer Vision and Pattern Recognition 1.5k
- Media Technology 700
- Artificial Intelligence 522
- Biomedical Engineering 518
- Computer Networks and Communications 373
Countries citing papers authored by Adil Khan
This map shows the geographic impact of Adil Khan'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 Adil Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adil Khan more than expected).
Fields of papers citing papers by Adil Khan
This network shows the impact of papers produced by Adil Khan. 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 Adil Khan. The network helps show where Adil Khan may publish in the future.
Co-authorship network of co-authors of Adil Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Adil Khan. A scholar is included among the top collaborators of Adil Khan 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 Adil Khan. Adil Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 31 | |
| 12 | Post-training Iterative Hierarchical Data Augmentation for Deep Networks | 1 |
| 13 | Antimicrobial Activity and Biomedical Application of Sambucus wightiana Phenolic Extract against Gram Positive and Gram-Negative Strains of Bacteria | 1 |
| 14 | 27 | |
| 15 | 15 | |
| 16 | Hyperspectral Band Selection Using Unsupervised Non-Linear Deep Auto Encoder to Train External Classifiers. | 5 |
| 17 | 1 | |
| 18 | 14 | |
| 19 | 24 | |
| 20 | Ontology Evolution and Challenges | 19 |
About Adil Khan
Adil Khan is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 100 papers that have together received 2.6k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (23 papers), Context-Aware Activity Recognition Systems (19 papers) and Face and Expression Recognition (11 papers). The work is most often cited by research in Media Technology (700 citations), Computer Vision and Pattern Recognition (1.5k citations) and Human-Computer Interaction (114 citations). Adil Khan has collaborated with scholars based in Russia, South Korea and United Kingdom. Frequent co-authors include Muhammad Ahmad, Young-Koo Lee, Manuel Mazzara, Salvatore Distefano, Tae‐Seong Kim, Sungyoung Lee, T.-S. Kim, Muhammad Hameed Siddiqi, Rahman Ali and S. Y. Lee. Their work appears in journals such as PLoS ONE, Chemical Engineering Journal and IEEE Transactions on Geoscience and Remote Sensing.
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.