D. Hush

2.6k total citations · 1 hit paper
42 papers, 1.8k citations indexed

About

D. Hush is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, D. Hush has authored 42 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 11 papers in Signal Processing and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in D. Hush's work include Neural Networks and Applications (16 papers), Blind Source Separation Techniques (6 papers) and Advanced SAR Imaging Techniques (6 papers). D. Hush is often cited by papers focused on Neural Networks and Applications (16 papers), Blind Source Separation Techniques (6 papers) and Advanced SAR Imaging Techniques (6 papers). D. Hush collaborates with scholars based in United States, South Korea and Brazil. D. Hush's co-authors include B.G. Horne, Carol Wood, Patrick Kelly, Clint Scovel, Ingo Steinwart, T. M. Cannon, Michael Cannon, N. Ahmed, S.D. Stearns and Radu‐Codruţ David and has published in prestigious journals such as IEEE Transactions on Information Theory, The Journal of the Acoustical Society of America and IEEE Signal Processing Magazine.

In The Last Decade

D. Hush

36 papers receiving 1.7k citations

Hit Papers

Progress in supervised neural networks 1993 2026 2004 2015 1993 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Progress in supervised neural networks
    1993 942 citations D. Hush, B.G. Horne profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
D. Hush United States 11 664 417 377 312 281 42 1.8k
M. N. S. Swamy Canada 23 622 0.9× 537 1.3× 542 1.4× 360 1.2× 158 0.6× 160 2.2k
Mark E. Oxley United States 18 611 0.9× 321 0.8× 214 0.6× 209 0.7× 169 0.6× 115 1.7k
Paul Honeiné France 21 844 1.3× 540 1.3× 277 0.7× 433 1.4× 322 1.1× 75 2.1k
James L. Melsa United States 14 483 0.7× 203 0.5× 259 0.7× 174 0.6× 133 0.5× 56 1.9k
Filip Mulier United States 8 906 1.4× 390 0.9× 152 0.4× 190 0.6× 90 0.3× 10 1.9k
Wenli Xu China 25 487 0.7× 990 2.4× 187 0.5× 164 0.5× 176 0.6× 158 2.3k
Erçan E. Kuruoğlu Italy 21 485 0.7× 552 1.3× 376 1.0× 387 1.2× 298 1.1× 149 1.9k
Jian Lü China 24 559 0.8× 1.2k 3.0× 216 0.6× 270 0.9× 450 1.6× 132 2.3k
G.L. Wise United States 15 298 0.4× 589 1.4× 189 0.5× 310 1.0× 99 0.4× 78 1.5k
Yu Zhou China 26 767 1.2× 576 1.4× 356 0.9× 87 0.3× 222 0.8× 167 2.2k

Countries citing papers authored by D. Hush

Since Specialization
Citations

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

Fields of papers citing papers by D. Hush

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Hush

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

All Works

20 of 20 papers shown
1.
Scovel, Clint, D. Hush, & Ingo Steinwart. (2007). Approximate Duality. Journal of Optimization Theory and Applications. 135(3). 429–443. 5 indexed citations
2.
Steinwart, Ingo, D. Hush, & Clint Scovel. (2006). An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels. IEEE Transactions on Information Theory. 52(10). 4635–4643. 147 indexed citations
3.
Ahmed, N., et al.. (2005). Detection of multiple sinusoids using an adaptive cascaded structure. 9. 199–202. 10 indexed citations
4.
Cannon, Mark, Michael Fugate, D. Hush, & Clint Scovel. (2003). Selecting a restoration technique to minimize OCR error. IEEE Transactions on Neural Networks. 14(3). 478–490. 5 indexed citations
5.
6.
Hush, D., et al.. (2002). Statistical analysis of a change detector based on image modeling of difference picture. International Conference on Acoustics, Speech, and Signal Processing. 2185–2188.
7.
Hush, D., Chaouki T. Abdallah, & B.G. Horne. (2002). Recursive neural networks for signal processing and control. UNM’s Digital Repository (University of New Mexico). 523–532. 1 indexed citations
8.
Abdallah, Chaouki T., Dalton S. Arantes, Gregory L. Heileman, et al.. (2002). Interactive DSP course development/teaching environment. UNM’s Digital Repository (University of New Mexico). 3. 2249–2252. 6 indexed citations
9.
Magotra, N., et al.. (2002). Seismic signal discrimination using adaptive system parameters. 84–87. 2 indexed citations
10.
Hush, D., et al.. (2002). An artificial retina for SAR object recognition. 22. 89–94. 1 indexed citations
11.
Hush, D., et al.. (1998). Statistical modeling of targets and clutter in single-look non-polarimetric SAR imagery. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 9 indexed citations
12.
Hush, D. & B.G. Horne. (1998). Efficient algorithms for function approximation with piecewise linear sigmoidal networks. IEEE Transactions on Neural Networks. 9(6). 1129–1141. 38 indexed citations
13.
Abdallah, Chaouki T., et al.. (1996). Error bounds in constructive approximation. Dialnet (Universidad de la Rioja). 24–28. 2 indexed citations
14.
Kelly, Patrick, T. M. Cannon, & D. Hush. (1995). Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approach. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2420. 238–238. 95 indexed citations
15.
Koch, Mark W., et al.. (1992). Feature discovery via neural networks for object recognition in SAR imagery. NASA STI/Recon Technical Report N. 92. 26902. 2 indexed citations
16.
Hush, D., et al.. (1992). Constrained-neural-network architectures for target recognition. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1709. 96–96. 1 indexed citations
17.
Etter, D.M. & D. Hush. (1987). A new technique for adaptive frequency estimation and tracking. IEEE Transactions on Acoustics Speech and Signal Processing. 35(4). 561–564. 12 indexed citations
18.
Hush, D. & G.W. Donohoe. (1987). Object tracking in the 2D image plane. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations
19.
20.
Ahmed, N., et al.. (1983). Second-order adaptive infinite impulse response filter. 2 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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