Luke M. Davis

516 total citations
3 papers, 315 citations indexed

About

Luke M. Davis is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Luke M. Davis has authored 3 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Signal Processing, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Artificial Intelligence. Recurrent topics in Luke M. Davis's work include Time Series Analysis and Forecasting (2 papers), Human Pose and Action Recognition (1 paper) and Anomaly Detection Techniques and Applications (1 paper). Luke M. Davis is often cited by papers focused on Time Series Analysis and Forecasting (2 papers), Human Pose and Action Recognition (1 paper) and Anomaly Detection Techniques and Applications (1 paper). Luke M. Davis collaborates with scholars based in United Kingdom. Luke M. Davis's co-authors include Jason Lines, Anthony Bagnall, Jon Hills, Barry-John Theobald and Andoni P. Toms and has published in prestigious journals such as International Journal of Neural Systems.

In The Last Decade

Luke M. Davis

3 papers receiving 310 citations

Peers

Luke M. Davis

SP

AI

EE

CVPR

MSOR

Kaveh Kamgar United States

Sergey Malinchik United States

Zoltan Geler Serbia

Makoto Imamura Japan

Michele Linardi France

Atsuhiko Kai Japan

Maria Kontaki Greece

Mourad Khayati Switzerland

Phanwadee Sinthong United States

Kaveh Kamgar United States

Luke M. Davis

164 ×0.6

SP

132 ×0.7

AI

51 ×0.6

EE

25 ×0.8

CVPR

5 ×0.2

MSOR

Citations per year, relative to Luke M. Davis Luke M. Davis (= 1×) peers Kaveh Kamgar

Countries citing papers authored by Luke M. Davis

Since Specialization

Citations

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

Fields of papers citing papers by Luke M. Davis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luke M. Davis. 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 Luke M. Davis. The network helps show where Luke M. Davis may publish in the future.

Co-authorship network of co-authors of Luke M. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of Luke M. Davis. A scholar is included among the top collaborators of Luke M. Davis 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 Luke M. Davis. Luke M. Davis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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3 of 3 papers shown

1.

Bagnall, Anthony, Luke M. Davis, Jon Hills, & Jason Lines. (2012). Transformation Based Ensembles for Time Series Classification. 307–318. 65 indexed citations

2.

Lines, Jason, Luke M. Davis, Jon Hills, & Anthony Bagnall. (2012). A shapelet transform for time series classification. 289–297. 237 indexed citations

3.

Davis, Luke M., Barry-John Theobald, Jason Lines, Andoni P. Toms, & Anthony Bagnall. (2012). ON THE SEGMENTATION AND CLASSIFICATION OF HAND RADIOGRAPHS. International Journal of Neural Systems. 22(5). 1250020–1250020. 13 indexed citations

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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