W. Philip Kegelmeyer

28 papers and 16.5k indexed citations i.

About

W. Philip Kegelmeyer is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, W. Philip Kegelmeyer has authored 28 papers receiving a total of 16.5k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 7 papers in Information Systems and 4 papers in Signal Processing. Recurrent topics in W. Philip Kegelmeyer’s work include Machine Learning and Data Classification (8 papers), Anomaly Detection Techniques and Applications (8 papers) and Adaptation to Concept Drift in Data Streams (7 papers). W. Philip Kegelmeyer is often cited by papers focused on Machine Learning and Data Classification (8 papers), Anomaly Detection Techniques and Applications (8 papers) and Adaptation to Concept Drift in Data Streams (7 papers). W. Philip Kegelmeyer collaborates with scholars based in United States. W. Philip Kegelmeyer's co-authors include Kevin W. Bowyer, Lawrence Hall, Nitesh V. Chawla, K. Woods, Robert E. Banfield, T. Ryan Hoens, David A. Cieslak, Argye Hillis, Mark W. Riggs and Jeffrey L. Solka and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Computational Physics and Radiology.

In The Last Decade

Co-authorship network of co-authors of W. Philip Kegelmeyer i

Fields of papers citing papers by W. Philip Kegelmeyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by W. Philip Kegelmeyer. 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 W. Philip Kegelmeyer. The network helps show where W. Philip Kegelmeyer may publish in the future.

Countries citing papers authored by W. Philip Kegelmeyer

Since Specialization
Citations

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

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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