Muhammad Muneeb Ullah
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Video Analysis and Summarization
- Multimodal Machine Learning Applications
- Advanced Vision and Imaging
- Human-Computer Interaction top 2%
- Hand Gesture Recognition Systems
Papers in
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- Human Pose and Action Recognition 3
- Advanced Image and Video Retrieval Techniques 2
- Video Surveillance and Tracking Methods 2
- Image Retrieval and Classification Techniques 2
- Video Analysis and Summarization 1
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- Software-Defined Networks and 5G 1
- Co-authors
- Ivan Laptev (2 shared papers)Heng Wang (1 shared paper)Alexander Kläser (1 shared paper)Cordelia Schmid (1 shared paper)Barbara Caputo (2 shared papers)Izaz Ahmad Khan (1 shared paper)Syed Adeel Ali Shah (1 shared paper)Francesco Orabona (1 shared paper)
- Journals
- HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (1 paper)
- Partner nations
- SwitzerlandFrancePakistan
In The Last Decade
Muhammad Muneeb Ullah
6 papers receiving 943 citations
Muhammad Muneeb Ullah's Hit Papers
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 929
- Human-Computer Interaction 170
- Artificial Intelligence 419
- Biomedical Engineering 237
- Computational Mathematics 2
Countries citing papers authored by Muhammad Muneeb Ullah
This map shows the geographic impact of Muhammad Muneeb Ullah'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 Muneeb Ullah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Muneeb Ullah more than expected).
Fields of papers citing papers by Muhammad Muneeb Ullah
This network shows the impact of papers produced by Muhammad Muneeb Ullah. 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 Muneeb Ullah. The network helps show where Muhammad Muneeb Ullah may publish in the future.
Co-authors
The 11 scholars most cited alongside Muhammad Muneeb Ullah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Evaluation of local spatio-temporal features for action recognition Hit paper breakdown → | 2009 | 895 |
| 2 | 2010 | 72 | |
| 3 | 2009 | 4 | |
| 4 | 2019 | 2 | |
| 5 | The COLD Database | 2007 | 2 |
| 6 | 2019 | 2 |
About Muhammad Muneeb Ullah
Muhammad Muneeb Ullah is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Aerospace Engineering and Biomedical Engineering, having authored 6 papers that have together received 977 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Video Surveillance and Tracking Methods (2 papers), Image Retrieval and Classification Techniques (2 papers), Anomaly Detection Techniques and Applications (1 paper), Video Analysis and Summarization (1 paper), Gait Recognition and Analysis (1 paper) and Software-Defined Networks and 5G (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (929 citations), Human-Computer Interaction (170 citations), Artificial Intelligence (419 citations), Biomedical Engineering (237 citations) and Computational Mathematics (2 citations). Muhammad Muneeb Ullah has collaborated with scholars based in Switzerland, France and Pakistan. Frequent co-authors include Ivan Laptev, Heng Wang, Alexander Kläser, Cordelia Schmid, Barbara Caputo, Izaz Ahmad Khan, Syed Adeel Ali Shah, Francesco Orabona, Patric Jensfelt and Andrzej Pronobis. Their work appears in journals such as HAL (Le Centre pour la Communication Scientifique Directe) and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.