K.M. Curtis
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Signal Processing top 10%
- Biomedical Engineering
- Co-authors
- Barrie Hayes‐GillMichael P. CravenAdnan KhashmanAthanassios SkodrasNick CampbellGareth J. F. JonesMark G. KellyJohn Orton
- Topics
- Neural Networks and Applications (17 papers)Speech Recognition and Synthesis (7 papers)Image Retrieval and Classification Techniques (7 papers)
- Partner nations
- United KingdomUnited StatesIreland
In The Last Decade
K.M. Curtis
43 papers receiving 323 citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 170
- Computer Vision and Pattern Recognition 162
- Electrical and Electronic Engineering 78
- Signal Processing 52
- Biomedical Engineering 30
Countries citing papers authored by K.M. Curtis
This map shows the geographic impact of K.M. Curtis'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 K.M. Curtis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K.M. Curtis more than expected).
Fields of papers citing papers by K.M. Curtis
This network shows the impact of papers produced by K.M. Curtis. 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 K.M. Curtis. The network helps show where K.M. Curtis may publish in the future.
Co-authorship network of co-authors of K.M. Curtis
This figure shows the co-authorship network connecting the top 25 collaborators of K.M. Curtis. A scholar is included among the top collaborators of K.M. Curtis 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 K.M. Curtis. K.M. Curtis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains | 0 |
| 2 | TRECVID 2018: Benchmarking Video Activity Detection, Video Captioning and Matching, Video Storytelling Linking and Video Search | 13 |
| 3 | DCU ADAPT @ TRECVid 2015: Video Hyperlinking Task. | 1 |
| 4 | 12 | |
| 5 | 3 | |
| 6 | 8 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 1 | |
| 11 | 7 | |
| 12 | 6 | |
| 13 | 1 | |
| 14 | 150 | |
| 15 | 48 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 7 | |
| 19 | 0 | |
| 20 | 4 |
About K.M. Curtis
K.M. Curtis is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 50 papers that have together received 363 indexed citations. Recurring topics across this work include Neural Networks and Applications (17 papers), Speech Recognition and Synthesis (7 papers) and Image Retrieval and Classification Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (162 citations), Artificial Intelligence (170 citations) and Signal Processing (52 citations). K.M. Curtis has collaborated with scholars based in United Kingdom, United States and Ireland. Frequent co-authors include Barrie Hayes‐Gill, Michael P. Craven, Adnan Khashman, Athanassios Skodras, Nick Campbell, Gareth J. F. Jones, Mark G. Kelly, John Orton, V. Fotopoulos and Halis Altun. Their work appears in journals such as Pattern Recognition, Electronics Letters and Plant Cell Reports.
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.