Muhammad Haris Khan
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Biomedical Engineering
- Neurology top 5%
- Co-authors
- Fahad Shahbaz KhanFahad ShamshadSyed Waqas ZamirMunawar HayatHuazhu FuSalman KhanYanwei PangLing Shao
- Topics
- Advanced Neural Network Applications (9 papers)Video Surveillance and Tracking Methods (8 papers)Face recognition and analysis (6 papers)
- Partner nations
- PakistanUnited Arab EmiratesUnited States
In The Last Decade
Muhammad Haris Khan
56 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Computer Vision and Pattern Recognition 796
- Artificial Intelligence 533
- Radiology, Nuclear Medicine and Imaging 354
- Biomedical Engineering 167
- Neurology 144
Countries citing papers authored by Muhammad Haris Khan
This map shows the geographic impact of Muhammad Haris 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 Muhammad Haris Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Haris Khan more than expected).
Fields of papers citing papers by Muhammad Haris Khan
This network shows the impact of papers produced by Muhammad Haris 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 Muhammad Haris Khan. The network helps show where Muhammad Haris Khan may publish in the future.
Co-authorship network of co-authors of Muhammad Haris Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Haris Khan. A scholar is included among the top collaborators of Muhammad Haris 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 Muhammad Haris Khan. Muhammad Haris 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 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 6 | |
| 13 | 116 | |
| 14 | 6 | |
| 15 | 5 | |
| 16 | SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection | 30 |
| 17 | 16 | |
| 18 | Cross-Domain Transferability of Adversarial Perturbations | 6 |
| 19 | 2 | |
| 20 | A Probabilistic Framework for Patch based Vehicle Type Recognition. | 12 |
About Muhammad Haris Khan
Muhammad Haris Khan is a scholar working on Computer Vision and Pattern Recognition, Neurology and Signal Processing, having authored 71 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Video Surveillance and Tracking Methods (8 papers) and Face recognition and analysis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (796 citations), Health Informatics (35 citations) and Neurology (144 citations). Muhammad Haris Khan has collaborated with scholars based in Pakistan, United Arab Emirates and United States. Frequent co-authors include Fahad Shahbaz Khan, Fahad Shamshad, Syed Waqas Zamir, Munawar Hayat, Huazhu Fu, Salman Khan, Yanwei Pang, Ling Shao, Rao Muhammad Anwer and Jin Xie. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurology and Scientific Reports.
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.