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
- Image Retrieval and Classification Techniques 2
- Video Surveillance and Tracking Methods 2
- Video Analysis and Summarization 1
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- Software-Defined Networks and 5G 1
- Co-authors
- Ivan LaptevCordelia SchmidAlexander KläserHeng WangBarbara CaputoFrancesco OrabonaSyed Adeel Ali ShahAndrzej Pronobis
- Journals
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- SwitzerlandPakistanFrance
In The Last Decade
Muhammad Muneeb Ullah
6 papers receiving 937 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 930
- Human-Computer Interaction 169
- Artificial Intelligence 421
- Biomedical Engineering 239
- 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-authorship network
The 10 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 | 2019 | 2 | |
| 2 | 2019 | 2 | |
| 3 | 2010 | 72 | |
| 4 | 2009 | 4 | |
| 5 | Evaluation of local spatio-temporal features for action recognition Hit paper breakdown → | 2009 | 893 |
| 6 | The COLD Database | 2007 | 2 |
About Muhammad Muneeb Ullah
Muhammad Muneeb Ullah is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Aerospace Engineering, Artificial Intelligence and Biomedical Engineering, having authored 6 papers that have together received 975 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Image Retrieval and Classification Techniques (2 papers), Video Surveillance and Tracking Methods (2 papers), Software-Defined Networks and 5G (1 paper), Video Analysis and Summarization (1 paper), Gait Recognition and Analysis (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (930 citations), Human-Computer Interaction (169 citations), Artificial Intelligence (421 citations), Biomedical Engineering (239 citations) and Computational Mathematics (2 citations). Muhammad Muneeb Ullah has collaborated with scholars based in Switzerland, Pakistan and France. Frequent co-authors include Ivan Laptev, Cordelia Schmid, Alexander Kläser, Heng Wang, Barbara Caputo, Francesco Orabona, Syed Adeel Ali Shah, Andrzej Pronobis, Jie Luo and Patric Jensfelt. Their work appears in journals such as Infoscience (Ecole Polytechnique Fédérale de Lausanne) and HAL (Le Centre pour la Communication Scientifique Directe).
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.