Ian Nabney
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Control and Systems Engineering top 10%
- Molecular Biology
- Co-authors
- Peter TiňoGeorge VogiatzisEsther CrawleyWajahat KazmiYi SunTom WilkinsonJames DoddRichard C. Burgess
- Topics
- Neural Networks and Applications (5 papers)Sleep and related disorders (3 papers)Handwritten Text Recognition Techniques (3 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Ian Nabney
18 papers receiving 788 citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 285
- Computer Vision and Pattern Recognition 162
- Signal Processing 97
- Control and Systems Engineering 88
- Molecular Biology 78
Countries citing papers authored by Ian Nabney
This map shows the geographic impact of Ian Nabney'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 Ian Nabney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Nabney more than expected).
Fields of papers citing papers by Ian Nabney
This network shows the impact of papers produced by Ian Nabney. 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 Ian Nabney. The network helps show where Ian Nabney may publish in the future.
Co-authorship network of co-authors of Ian Nabney
This figure shows the co-authorship network connecting the top 25 collaborators of Ian Nabney. A scholar is included among the top collaborators of Ian Nabney 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 Ian Nabney. Ian Nabney 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 | 3 | |
| 4 | 6 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 13 | |
| 10 | 21 | |
| 11 | 6 | |
| 12 | 2 | |
| 13 | 8 | |
| 14 | 20 | |
| 15 | The DeCCo project papers II Z Specification of Asp | 0 |
| 16 | Netlab: Algorithms for Pattern Recognitionbreakdown → | 698 |
| 17 | 2 | |
| 18 | GTM-based data visualisation with incomplete data | 2 |
| 19 | 64 | |
| 20 | The Learning Dynamcis of a Universal Approximator | 1 |
About Ian Nabney
Ian Nabney is a scholar working on Applied Psychology, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 860 indexed citations. Recurring topics across this work include Neural Networks and Applications (5 papers), Sleep and related disorders (3 papers) and Handwritten Text Recognition Techniques (3 papers). The work is most often cited by research in Signal Processing (97 citations), Artificial Intelligence (285 citations) and Computer Vision and Pattern Recognition (162 citations). Ian Nabney has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Peter Tiňo, George Vogiatzis, Esther Crawley, Wajahat Kazmi, Yi Sun, Tom Wilkinson, James Dodd, Richard C. Burgess, Caroline Van Holsbeke and Yulan He. Their work appears in journals such as Sensors, Frontiers in Psychology and Journal of Medical Internet Research.
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.