Jon Curtis

473 citations
11 papers · 239 indexed · h-index 6

Jon Curtis

11 papers receiving 217 citations

Peers

Jon Curtis
Comparison fields: 5 of 56
  • Artificial Intelligence 87
  • Molecular Biology 122
  • Computer Vision and Pattern Recognition 28
  • Signal Processing 10
  • Information Systems 20
Replace Roy Varshavsky with:
Roy Varshavsky Israel
Cinzia Pizzi Italy
Chirag Jain United States
Stefan Burkhardt Germany
Emre Sefer Türkiye
Favorisen Rosyking Lumbanraja Indonesia
Jan Holub Czechia
Christine Sinoquet France
Avdesh Mishra United States
Manfred Schimmler Germany
Jon Curtis relative to Roy Varshavsky Israel Roy Varshavsky's profile →
Citations per field
00.5×1.6×
Roy Varshavsky · 1×
Citations per year

Countries citing papers authored by Jon Curtis

Since Specialization
Citations

This map shows the geographic impact of Jon 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 Jon Curtis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Curtis more than expected).

Fields of papers citing papers by Jon Curtis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jon 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 Jon Curtis. The network helps show where Jon Curtis may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jon Curtis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jon Curtis Line = papers co-authored together Jon Curtis links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 20224
2
SRI-Sarnoff AURORA System at TRECVID 2013 Multimedia Event Detection and Recounting.
20135
3
SRI-Sarnoff AURORA System at TRECVID 2012 Multimedia Event Detection and Recounting.
201214
4
Team SRI-Sarnoff 's AURORA System @ TRECVID 2011
20113
5
Methods of Rule Acquisition in the TextLearner System.
20095
6 200623
7 200621
8 200530
9 20043
10 199451
11 199380

About Jon Curtis

Jon Curtis is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 11 papers that have together received 239 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Topic Modeling (4 papers), Semantic Web and Ontologies (3 papers), Video Analysis and Summarization (3 papers), Multimodal Machine Learning Applications (2 papers), RNA and protein synthesis mechanisms (2 papers), Viral gastroenteritis research and epidemiology (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Artificial Intelligence (87 citations), Molecular Biology (122 citations) and Computer Vision and Pattern Recognition (28 citations). Jon Curtis has collaborated with scholars based in United Kingdom, Australia and Austria. Frequent co-authors include Hans Lehrach, Sebastian Meier‐Ewert, David Baxter, John Cabral, Michael Witbrock, David Schneider, Cynthia Matuszek, Benjamin Elizalde, Mubarak Shah and Jingen Liu. Their work appears in journals such as Scientific Reports, Bioresource Technology, Journal of Biotechnology, Nature and TRECVID.

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.

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