Hayat Ullah
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Plant Science
- Computer Networks and Communications top 10%
- Media Technology top 5%
- Co-authors
- Muhammad Zubair AsgharArslan MunirKhan MuhammadVictor Hugo C. de AlbuquerqueDaniyal AlghazzawiOmaimah BamasagAbdu GumaeiMabrook Al‐Rakhami
- Topics
- Video Surveillance and Tracking Methods (7 papers)Image Enhancement Techniques (6 papers)Anomaly Detection Techniques and Applications (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Transactions on Image Processing
- Partner nations
- United StatesSouth KoreaPakistan
In The Last Decade
Hayat Ullah
23 papers receiving 641 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 285
- Artificial Intelligence 178
- Plant Science 146
- Computer Networks and Communications 91
- Media Technology 61
Countries citing papers authored by Hayat Ullah
This map shows the geographic impact of Hayat 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 Hayat Ullah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hayat Ullah more than expected).
Fields of papers citing papers by Hayat Ullah
This network shows the impact of papers produced by Hayat 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 Hayat Ullah. The network helps show where Hayat Ullah may publish in the future.
Co-authorship network of co-authors of Hayat Ullah
This figure shows the co-authorship network connecting the top 25 collaborators of Hayat Ullah. A scholar is included among the top collaborators of Hayat Ullah 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 Hayat Ullah. Hayat Ullah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 26 | |
| 6 | 43 | |
| 7 | 6 | |
| 8 | 10 | |
| 9 | 93 | |
| 10 | 7 | |
| 11 | 4 | |
| 12 | 10 | |
| 13 | 2 | |
| 14 | 17 | |
| 15 | 91 | |
| 16 | 16 | |
| 17 | 115 | |
| 18 | 16 | |
| 19 | 15 | |
| 20 | 3 |
About Hayat Ullah
Hayat Ullah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Safety, Risk, Reliability and Quality, having authored 23 papers that have together received 667 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Image Enhancement Techniques (6 papers) and Anomaly Detection Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (285 citations), Media Technology (61 citations) and Artificial Intelligence (178 citations). Hayat Ullah has collaborated with scholars based in United States, South Korea and Pakistan. Frequent co-authors include Muhammad Zubair Asghar, Arslan Munir, Khan Muhammad, Victor Hugo C. de Albuquerque, Daniyal Alghazzawi, Omaimah Bamasag, Abdu Gumaei, Mabrook Al‐Rakhami, Asad Masood Khattak and Muhammad Sajjad. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.
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.