Andrew Secker
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Molecular Biology
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Co-authors
- David TaubmanAlex A. FreitasJon TimmisDarren R. FlowerMatthew N. DaviesNishanth SastryEdward ClarkDmytro Karamshuk
- Topics
- Machine Learning in Bioinformatics (10 papers)Image and Signal Denoising Methods (6 papers)Advanced Data Compression Techniques (6 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- BioinformaticsIEEE Transactions on Image ProcessingIEEE Journal on Selected Areas in Communications
- Partner nations
- United KingdomAustraliaDenmark
In The Last Decade
Andrew Secker
29 papers receiving 884 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 470
- Signal Processing 315
- Molecular Biology 253
- Artificial Intelligence 110
- Computer Networks and Communications 100
Countries citing papers authored by Andrew Secker
This map shows the geographic impact of Andrew Secker'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 Andrew Secker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Secker more than expected).
Fields of papers citing papers by Andrew Secker
This network shows the impact of papers produced by Andrew Secker. 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 Andrew Secker. The network helps show where Andrew Secker may publish in the future.
Co-authorship network of co-authors of Andrew Secker
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Secker. A scholar is included among the top collaborators of Andrew Secker 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 Andrew Secker. Andrew Secker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | Global Under-Resourced Media Translation (GoURMET) | 3 |
| 3 | 18 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 13 | |
| 7 | 26 | |
| 8 | 6 | |
| 9 | 24 | |
| 10 | 5 | |
| 11 | 28 | |
| 12 | 11 | |
| 13 | 35 | |
| 14 | 69 | |
| 15 | 69 | |
| 16 | 30 | |
| 17 | 7 | |
| 18 | 57 | |
| 19 | 173 | |
| 20 | 4 |
About Andrew Secker
Andrew Secker is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 29 papers that have together received 937 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (10 papers), Image and Signal Denoising Methods (6 papers) and Advanced Data Compression Techniques (6 papers). The work is most often cited by research in Signal Processing (315 citations), Computer Vision and Pattern Recognition (470 citations) and Computer Networks and Communications (100 citations). Andrew Secker has collaborated with scholars based in United Kingdom, Australia and Denmark. Frequent co-authors include David Taubman, Alex A. Freitas, Jon Timmis, Darren R. Flower, Matthew N. Davies, Nishanth Sastry, Edward Clark, Dmytro Karamshuk, Matthew N Davies and David E. Gloriam. Their work appears in journals such as Bioinformatics, IEEE Transactions on Image Processing and IEEE Journal on Selected Areas in Communications.
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.