Anthony Kuh

1.3k citations
80 papers · 790 · h-index 15

Impact in

    • Blind Source Separation Techniques
    • Neural Networks and Applications
    • Privacy-Preserving Technologies in Data
    • Solar Radiation and Photovoltaics
    • Data Stream Mining Techniques

Papers in

Anthony Kuh

72 papers receiving 758 citations

Peers

Anthony Kuh
Comparison fields: 5 of 95
  • Signal Processing 151
  • Artificial Intelligence 389
  • Developmental Biology 17
  • Control and Systems Engineering 158
  • Architecture 9
Replace Paul M. Baggenstoss with:
Paul M. Baggenstoss United States
Guoqiang Zhang Australia
Mahesh K. Banavar United States
Tien Pham United States
Madhusudana Shashanka United States
GE Hinton Canada
David Rappaport Canada
John Sum Hong Kong
Zhengguang Xu China
Feng Su China
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Citations per field
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Paul M. Baggenstoss · 1×
Citations per year

Countries citing papers authored by Anthony Kuh

Since Specialization
Citations

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

Fields of papers citing papers by Anthony Kuh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Anthony Kuh, 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 Anthony Kuh Line = papers co-authored together Anthony Kuh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200899
2 201160
3
Learning Time-varying Concepts
199047
4 199247
5 198947
6 201835
7 201133
8 201226
9 201124
10 200124
11 201317
12 200217
13 201517
14 202016
15 200216
16 202214
17 200914
18 202213
19 202212
20 201612

About Anthony Kuh

Anthony Kuh is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 80 papers that have together received 790 indexed citations. Recurring topics across this work include Neural Networks and Applications (19 papers), Advanced Adaptive Filtering Techniques (16 papers), Distributed Sensor Networks and Detection Algorithms (9 papers), Privacy-Preserving Technologies in Data (8 papers), Solar Radiation and Photovoltaics (8 papers), Energy Load and Power Forecasting (8 papers), Smart Grid Energy Management (8 papers) and Image and Signal Denoising Methods (8 papers). The work is most often cited by research in Signal Processing (151 citations), Artificial Intelligence (389 citations), Developmental Biology (17 citations), Control and Systems Engineering (158 citations) and Architecture (9 citations). Anthony Kuh has collaborated with scholars based in United States, Norway and United Kingdom. Frequent co-authors include Danilo P. Mandic, B. Dickinson, A. Kavcic, Ying Hu, Thomas Petsche, Su Lee Goh, Kazuyuki Aihara, Stefan Werner, Yih-Fang Huang and Matthias Fripp. Their work appears in journals such as Renewable Energy, IEEE Transactions on Signal Processing, IEEE Internet of Things Journal, Journal of Engineering Education and Neural Networks.

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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