Gary A. Shaw

38 papers receiving 2.8k citations

Gary A. Shaw's Hit Papers

Hyperspectral Image Processing for Automatic Target Detection Applications 2003 · 588 citations
5880+8+16Years since publication250500750

Peers

Gary A. Shaw
Comparison fields: 5 of 118
  • Media Technology 2.1k
  • Atmospheric Science 897
  • Analytical Chemistry 454
  • Computer Vision and Pattern Recognition 614
  • Aerospace Engineering 647
Replace Michael T. Eismann with:
Michael T. Eismann United States
Jerry E. Solomon United States
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Citations per year

Countries citing papers authored by Gary A. Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Gary A. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gary A. Shaw. 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 Gary A. Shaw. The network helps show where Gary A. Shaw may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Detection algorithms for hyperspectral imaging applications
Hit paper breakdown →
2002849
2
Hyperspectral Image Processing for Automatic Target Detection Applications
Hit paper breakdown →
2003588
3
Spectral Imaging for Remote Sensing
2003350
4 2002294
5 2001252
6 200073
7 200666
8 200961
9 200057
10 200556
11 200053
12 200334
13 200132
14
On the Statistics of Hyperspectral Imaging Data
200130
15 200425
16 200224
17 200420
18 200117
19 200115
20
Design, stability and performance of two-dimensional recursive digital filters
19798

About Gary A. Shaw

Gary A. Shaw is a scholar working on Electrical and Electronic Engineering, Media Technology, Aerospace Engineering, Instrumentation and Artificial Intelligence, having authored 42 papers that have together received 3.0k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (12 papers), Optical Wireless Communication Technologies (8 papers), Advanced Optical Sensing Technologies (8 papers), Infrared Target Detection Methodologies (6 papers), Spectroscopy and Chemometric Analyses (4 papers), Geochemistry and Geologic Mapping (4 papers), Digital Filter Design and Implementation (3 papers) and Embedded Systems Design Techniques (3 papers). The work is most often cited by research in Media Technology (2.1k citations), Atmospheric Science (897 citations), Analytical Chemistry (454 citations), Computer Vision and Pattern Recognition (614 citations) and Aerospace Engineering (647 citations). Gary A. Shaw has collaborated with scholars based in United States, Netherlands and Japan. Frequent co-authors include Dimitris G. Manolakis, David Marden, Hsiao-hua K. Burke, Andrew M. Siegel, Nirmal Keshava, John P. Kerekes, Michael K. Griffin, Sumanth Kaushik, Stanislav I. Soloviev and Alexey Vert. Their work appears in journals such as IEEE Signal Processing Magazine, IEEE Sensors Journal, IEEE Transactions on Automatic Control, Proceedings of the IEEE and Journal of Spacecraft and Rockets.

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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