James Petterson

743 citations
15 papers · 462 · h-index 9

Impact in

    • Video Surveillance and Tracking Methods
    • Advanced Image and Video Retrieval Techniques
    • Advanced Neural Network Applications
    • Text and Document Classification Technologies
    • Topic Modeling
    • Machine Learning and Algorithms
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques

Papers in

    • Text and Document Classification Technologies 3
    • Machine Learning and Data Classification 3
    • Machine Learning and Algorithms 3
    • Anomaly Detection Techniques and Applications 2
    • Natural Language Processing Techniques 2
    • Bayesian Modeling and Causal Inference 2
    • Video Surveillance and Tracking Methods 3
    • Advanced Image and Video Retrieval Techniques 3

James Petterson

14 papers receiving 440 citations

Peers

James Petterson
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 242
  • Artificial Intelligence 265
  • Media Technology 44
  • Signal Processing 37
  • General Social Sciences 9
Replace Cina Motamed with:
Cina Motamed France
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Jian Cao China
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Citations per field
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Citations per year

Countries citing papers authored by James Petterson

Since Specialization
Citations

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

Fields of papers citing papers by James Petterson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside James Petterson, 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 James Petterson Line = papers co-authored together James Petterson links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2009112
2 201191
3
Word Features for Latent Dirichlet Allocation
201060
4
Reverse Multi-Label Learning
201050
5
Submodular Multi-Label Learning
201134
6 201132
7 201123
8
Multitask Learning without Label Correspondences
201021
9
Distribution Matching for Transduction
200915
10 20128
11 20097
12 20137
13
Learning as MAP Inference in Discrete Graphical Models
20121
14 20121
15
Postwar figures of L'Ephémère : Yves Bonnefoy, Louis-René des Forêts, Jacques Dupin, André du Bouchet
20000

About James Petterson

James Petterson is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Statistical and Nonlinear Physics, having authored 15 papers that have together received 462 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (3 papers), Text and Document Classification Technologies (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Machine Learning and Data Classification (3 papers), Machine Learning and Algorithms (3 papers), Anomaly Detection Techniques and Applications (2 papers), Natural Language Processing Techniques (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (242 citations), Artificial Intelligence (265 citations), Media Technology (44 citations), Signal Processing (37 citations) and General Social Sciences (9 citations). James Petterson has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Tibério S. Caetano, Alex Smola, Rogério Feris, Behjat Siddiquie, Lisa M. Brown, Sharath Pankanti, John Langford, Qinfeng Shi, Gideon Dror and Yun Zhai. Their work appears in journals such as Journal of Machine Learning Research, IEEE Transactions on Multimedia, Romanic Review, ANU Open Research (Australian National University) and arXiv (Cornell University).

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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