Paul Fergus
- Artificial Intelligence top 5%
- Pediatrics, Perinatology and Child Health top 5%
- Cognitive Neuroscience top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Co-authors
- Dhiya Al‐JumeilyAbir HussainCarl ChalmersChelsea DobbinsKhaled Abdel‐AzizMadjid MerabtiShamaila IramSerge A. Wich
- Topics
- Context-Aware Activity Recognition Systems (22 papers)Neonatal and fetal brain pathology (8 papers)Wildlife Ecology and Conservation (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEProceedings of the IEEE
- Partner nations
- United KingdomNetherlandsFrance
In The Last Decade
Paul Fergus
117 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 162
- Artificial Intelligence 287
- Pediatrics, Perinatology and Child Health 281
- Cognitive Neuroscience 256
- Computer Vision and Pattern Recognition 232
- Biomedical Engineering 226
Countries citing papers authored by Paul Fergus
This map shows the geographic impact of Paul Fergus'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 Paul Fergus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Fergus more than expected).
Fields of papers citing papers by Paul Fergus
This network shows the impact of papers produced by Paul Fergus. 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 Paul Fergus. The network helps show where Paul Fergus may publish in the future.
Co-authorship network of co-authors of Paul Fergus
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Fergus. A scholar is included among the top collaborators of Paul Fergus 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 Paul Fergus. Paul Fergus 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 | 1 | |
| 3 | 11 | |
| 4 | 15 | |
| 5 | 67 | |
| 6 | 10 | |
| 7 | 13 | |
| 8 | 14 | |
| 9 | 18 | |
| 10 | 1 | |
| 11 | 28 | |
| 12 | 6 | |
| 13 | 57 | |
| 14 | 25 | |
| 15 | A Smart Framework for Predicting the Onset of Nocturnal Enuresis (PrONE) in Children and Young People | 1 |
| 16 | 10 | |
| 17 | 12 | |
| 18 | A hierarchically structured global data collection network | 1 |
| 19 | Controlling Networked Devices In Ubiquitous Computing Environments using Biofeedback | 1 |
| 20 | Distributed emergent semantics in P2P networks | 4 |
About Paul Fergus
Paul Fergus is a scholar working on Ecological Modeling, Computer Vision and Pattern Recognition and Occupational Therapy, having authored 123 papers that have together received 1.8k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (22 papers), Neonatal and fetal brain pathology (8 papers) and Wildlife Ecology and Conservation (8 papers). The work is most often cited by research in Health Informatics (54 citations), Health Information Management (119 citations) and Ecological Modeling (81 citations). Paul Fergus has collaborated with scholars based in United Kingdom, Netherlands and France. Frequent co-authors include Dhiya Al‐Jumeily, Abir Hussain, Carl Chalmers, Chelsea Dobbins, Khaled Abdel‐Aziz, Madjid Merabti, Abir Hussain, Shamaila Iram, Serge A. Wich and Mohammed Khalaf. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Proceedings of the IEEE.
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.