Mubarak Shah
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Biomedical Engineering top 10%
- Human-Computer Interaction top 2%
- Media Technology top 5%
- Co-authors
- Mikel RodríguezJaved AhmedRadu Tudor IonescuFlorinel-Alin CroitoruVlad HondruArslan BasharatSaad AliYaser Sheikh
- Topics
- Anomaly Detection Techniques and Applications (7 papers)Generative Adversarial Networks and Image Synthesis (6 papers)Human Pose and Action Recognition (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingInternational Journal of Computer Vision
- Partner nations
- United StatesAustraliaUnited Arab Emirates
In The Last Decade
Mubarak Shah
34 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 923
- Biomedical Engineering 338
- Human-Computer Interaction 151
- Media Technology 119
Countries citing papers authored by Mubarak Shah
This map shows the geographic impact of Mubarak Shah'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 Mubarak Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mubarak Shah more than expected).
Fields of papers citing papers by Mubarak Shah
This network shows the impact of papers produced by Mubarak Shah. 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 Mubarak Shah. The network helps show where Mubarak Shah may publish in the future.
Co-authorship network of co-authors of Mubarak Shah
This figure shows the co-authorship network connecting the top 25 collaborators of Mubarak Shah. A scholar is included among the top collaborators of Mubarak Shah 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 Mubarak Shah. Mubarak Shah 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | Foundation Models Defining a New Era in Vision: A Survey and Outlookbreakdown → | 41 |
| 6 | 12 | |
| 7 | 7 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 41 | |
| 13 | 3 | |
| 14 | 35 | |
| 15 | 59 | |
| 16 | 19 | |
| 17 | 9 | |
| 18 | 25 | |
| 19 | 16 | |
| 20 | A Computer Vision Framework for Analyzing Overhead and Computer Projections from Video of Lectures. | 1 |
About Mubarak Shah
Mubarak Shah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 40 papers that have together received 2.4k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (7 papers), Generative Adversarial Networks and Image Synthesis (6 papers) and Human Pose and Action Recognition (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Artificial Intelligence (923 citations) and Human-Computer Interaction (151 citations). Mubarak Shah has collaborated with scholars based in United States, Australia and United Arab Emirates. Frequent co-authors include Mikel Rodríguez, Javed Ahmed, Radu Tudor Ionescu, Florinel-Alin Croitoru, Vlad Hondru, Arslan Basharat, Saad Ali, Yaser Sheikh, Fahad Shahbaz Khan and Saeed Vahidian. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and International Journal of Computer Vision.
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.