Douglas L. Reilly

541 citations
5 papers · 294 indexed · h-index 3
Topics
Neural Networks and Applications (3 papers)Imbalanced Data Classification Techniques (1 paper)Image and Signal Denoising Methods (1 paper)
Journals
Biological CyberneticsHawaii International Conference on System SciencesProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
Partner nations
United States

In The Last Decade

Douglas L. Reilly

5 papers receiving 259 citations

Peers

Douglas L. Reilly
Comparison fields: 5 of 65
  • Artificial Intelligence 225
  • Computer Vision and Pattern Recognition 102
  • Control and Systems Engineering 44
  • Signal Processing 35
  • Cognitive Neuroscience 18
Replace J.H. Kim with:
J.H. Kim South Korea
K.M. Curtis United Kingdom
Fuad M. Alkoot Kuwait
Utpal Nandi India
Kuizhi Mei China
Joachim K. Anlauf Germany
Norbert Ádám Slovakia
Zhuoping Zhou United States
Reza Hassanpour Türkiye
Mohamed Morchid France
Douglas L. Reilly relative to J.H. Kim South Korea J.H. Kim's profile →
Citations per field
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J.H. Kim · 1×
Citations per year

Countries citing papers authored by Douglas L. Reilly

Since Specialization
Citations

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

Fields of papers citing papers by Douglas L. Reilly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Douglas L. Reilly. 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 Douglas L. Reilly. The network helps show where Douglas L. Reilly may publish in the future.

Co-authorship network of co-authors of Douglas L. Reilly

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

All Works

5 of 5 papers shown
#WorkIndexed citations
1 5
2
A NEURAL NETWORK VIDEO SENSOR APPLICATION FOR RAIL CROSSING SAFETY
1
3
Credit Card Fraud Detection with a Neural-Network
2
4 10
5 276

About Douglas L. Reilly

Douglas L. Reilly is a scholar working on Artificial Intelligence, Media Technology and Signal Processing, having authored 5 papers that have together received 294 indexed citations. Recurring topics across this work include Neural Networks and Applications (3 papers), Imbalanced Data Classification Techniques (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Artificial Intelligence (225 citations), Computer Vision and Pattern Recognition (102 citations) and Signal Processing (35 citations). Douglas L. Reilly has collaborated with scholars based in United States. Frequent co-authors include Leon N. Cooper, C. Elbaum, Christopher L. Scofield and Raymond D. Rimey. Their work appears in journals such as Biological Cybernetics, Hawaii International Conference on System Sciences and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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