Khan Muhammad
Impact in
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Advanced Steganography and Watermarking Techniques
- Advanced Neural Network Applications
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- Fire Detection and Safety Systems
Papers in
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- Video Surveillance and Tracking Methods 61
- Advanced Steganography and Watermarking Techniques 28
- Human Pose and Action Recognition 25
- Chaos-based Image/Signal Encryption 23
- Advanced Image and Video Retrieval Techniques 22
- Advanced Neural Network Applications 18
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- Anomaly Detection Techniques and Applications 29
- Co-authors
- Sung Wook Baik (64 shared papers)Amin Ullah (30 shared papers)Victor Hugo C. de Albuquerque (48 shared papers)Muhammad Husain As Sajjad (44 shared papers)Jamil Ahmad (19 shared papers)Salman Khan (10 shared papers)Javier Del Ser (30 shared papers)Jaime Lloret (14 shared papers)
- Journals
- IEEE Access (19 papers)IEEE Internet of Things Journal (17 papers)IEEE Transactions on Industrial Informatics (16 papers)Future Generation Computer Systems (15 papers)Multimedia Tools and Applications (9 papers)
- Partner nations
- South KoreaChinaPakistan
In The Last Decade
Khan Muhammad
251 papers receiving 15.3k citations
Khan Muhammad's Hit Papers
Peers
Comparison fields: 5 of 201
- Computer Vision and Pattern Recognition 7.2k
- Safety, Risk, Reliability and Quality 1.4k
- Artificial Intelligence 5.3k
- Neurology 1.2k
- Health Informatics 151
Countries citing papers authored by Khan Muhammad
This map shows the geographic impact of Khan Muhammad'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 Khan Muhammad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khan Muhammad more than expected).
Fields of papers citing papers by Khan Muhammad
This network shows the impact of papers produced by Khan Muhammad. 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 Khan Muhammad. The network helps show where Khan Muhammad may publish in the future.
Co-authors
The 25 scholars most cited alongside Khan Muhammad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 260 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Multi-grade brain tumor classification using deep CNN with extensive data augmentation Hit paper breakdown → | 2018 | 699 |
| 2 | Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features Hit paper breakdown → | 2017 | 607 |
| 3 | Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions Hit paper breakdown → | 2020 | 445 |
| 4 | Convolutional Neural Networks Based Fire Detection in Surveillance Videos Hit paper breakdown → | 2018 | 434 |
| 5 | Early fire detection using convolutional neural networks during surveillance for effective disaster management Hit paper breakdown → | 2017 | 406 |
| 6 | The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems Hit paper breakdown → | 2017 | 331 |
| 7 | Image based fruit category classification by 13-layer deep convolutional neural network and data augmentation Hit paper breakdown → | 2017 | 326 |
| 8 | Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey Hit paper breakdown → | 2020 | 314 |
| 9 | Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy Hit paper breakdown → | 2020 | 285 |
| 10 | 2018 | 264 | |
| 11 | 2019 | 237 | |
| 12 | 2018 | 228 | |
| 13 | 2020 | 216 | |
| 14 | Federated learning for COVID-19 screening from Chest X-ray images Hit paper breakdown → | 2021 | 216 |
| 15 | 2018 | 213 | |
| 16 | 2020 | 195 | |
| 17 | 2021 | 191 | |
| 18 | 2020 | 191 | |
| 19 | 2019 | 186 | |
| 20 | 2019 | 185 |
About Khan Muhammad
Khan Muhammad is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Safety, Risk, Reliability and Quality, Computer Networks and Communications and Information Systems, having authored 260 papers that have together received 15.9k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (61 papers), Anomaly Detection Techniques and Applications (29 papers), Advanced Steganography and Watermarking Techniques (28 papers), Human Pose and Action Recognition (25 papers), Chaos-based Image/Signal Encryption (23 papers), Advanced Image and Video Retrieval Techniques (22 papers), Advanced Neural Network Applications (18 papers) and Fire Detection and Safety Systems (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.2k citations), Safety, Risk, Reliability and Quality (1.4k citations), Artificial Intelligence (5.3k citations), Neurology (1.2k citations) and Health Informatics (151 citations). Khan Muhammad has collaborated with scholars based in South Korea, China and Pakistan. Frequent co-authors include Sung Wook Baik, Amin Ullah, Victor Hugo C. de Albuquerque, Muhammad Husain As Sajjad, Jamil Ahmad, Salman Khan, Javier Del Ser, Jaime Lloret, Irfan Mehmood and Arun Kumar Sangaiah. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, Future Generation Computer Systems and Multimedia Tools and Applications.
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.