Gregory W. Cook

427 total citations
36 papers, 272 citations indexed

About

Gregory W. Cook is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Gregory W. Cook has authored 36 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 16 papers in Signal Processing and 5 papers in Artificial Intelligence. Recurrent topics in Gregory W. Cook's work include Advanced Data Compression Techniques (14 papers), Video Coding and Compression Technologies (14 papers) and Image and Signal Denoising Methods (7 papers). Gregory W. Cook is often cited by papers focused on Advanced Data Compression Techniques (14 papers), Video Coding and Compression Technologies (14 papers) and Image and Signal Denoising Methods (7 papers). Gregory W. Cook collaborates with scholars based in United States, Spain and South Korea. Gregory W. Cook's co-authors include Edward J. Delp, Josep Prades-Nebot, D. F. Kerridge, Jeffrey L. Clendenon, Adele J. Filson, Vincent H. Gattone, Karen J. Miller, Paul A. Overbeek, Paul Salama and Robert L. Bacallao and has published in prestigious journals such as Biometrics, IEEE Transactions on Information Theory and IEEE Transactions on Image Processing.

In The Last Decade

Gregory W. Cook

35 papers receiving 249 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregory W. Cook United States 10 133 69 55 52 38 36 272
Sook Yoon South Korea 11 73 0.5× 132 1.9× 70 1.3× 73 1.4× 16 0.4× 14 313
Randy P. Broussard United States 11 192 1.4× 181 2.6× 22 0.4× 13 0.3× 45 1.2× 36 416
Eric B. Lum United States 15 551 4.1× 41 0.6× 34 0.6× 21 0.4× 3 0.1× 32 707
Lawrence Cayton United States 7 116 0.9× 52 0.8× 26 0.5× 20 0.4× 12 0.3× 9 245
Cheng Tai China 6 194 1.5× 17 0.2× 71 1.3× 18 0.3× 30 0.8× 11 355
Tae-Hyun Hwang United States 8 94 0.7× 25 0.4× 103 1.9× 13 0.3× 22 0.6× 19 268
Diwei Zhou United Kingdom 6 66 0.5× 21 0.3× 16 0.3× 8 0.2× 7 0.2× 24 315
M. Maes Netherlands 11 496 3.7× 114 1.7× 42 0.8× 10 0.2× 5 0.1× 16 562
Concettina Guerra United States 13 96 0.7× 8 0.1× 258 4.7× 18 0.3× 19 0.5× 38 454
Guy Katz Israel 8 40 0.3× 23 0.3× 24 0.4× 75 1.4× 20 0.5× 23 289

Countries citing papers authored by Gregory W. Cook

Since Specialization
Citations

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

Fields of papers citing papers by Gregory W. Cook

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregory W. Cook

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory W. Cook. A scholar is included among the top collaborators of Gregory W. Cook 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 Gregory W. Cook. Gregory W. Cook 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.
Cook, Gregory W., et al.. (2019). 68‐1: A Machine Learning Approach to Objective Image Quality Evaluation. SID Symposium Digest of Technical Papers. 50(1). 957–960. 1 indexed citations
2.
Cook, Gregory W., et al.. (2018). Brain sources estimation based on EEG and computer simulation technology (CST). Biomedical Signal Processing and Control. 46. 145–156. 5 indexed citations
3.
Cook, Gregory W., et al.. (2016). 18‐4: A Low Latency Compression Algorithm for Visually Lossless Display Stream Systems Using Temporal Differencing. SID Symposium Digest of Technical Papers. 47(1). 215–218. 1 indexed citations
4.
Cook, Gregory W. & Ton Kalker. (2013). The sparse discrete cosine transform with application to image compression. 9–12. 2 indexed citations
5.
Cook, Gregory W. & Ton Kalker. (2012). Low-complexity arbitrarily shaped transform and coefficient ordering method based on the four-point DCT. 2485–2488. 1 indexed citations
6.
Wang, Jingxin, et al.. (2009). Assessments of hardwood lumber edging, trimming, and grading practices of small sawmills in West Virginia.. Forest Products Journal. 59(5). 69–75. 2 indexed citations
7.
Prades-Nebot, Josep, Gregory W. Cook, & Edward J. Delp. (2006). An analysis of the efficiency of different SNR-scalable strategies for video coders. IEEE Transactions on Image Processing. 15(4). 848–864. 5 indexed citations
8.
Cook, Gregory W., et al.. (2006). Rate-distortion analysis of motion-compensated rate scalable video. IEEE Transactions on Image Processing. 15(8). 2170–2190. 19 indexed citations
9.
Prades-Nebot, Josep, et al.. (2005). Rate distortion performance of leaky prediction layered video coding: theoretic analysis and results. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5685. 315–315. 3 indexed citations
10.
Phillips, Carrie L., Karen J. Miller, Adele J. Filson, et al.. (2004). Renal Cysts of inv/inv Mice Resemble Early Infantile Nephronophthisis. Journal of the American Society of Nephrology. 15(7). 1744–1755. 61 indexed citations
11.
Salama, Paul, et al.. (2004). Rate distortion analysis of layered video coding by leaky prediction. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5308. 543–543. 7 indexed citations
12.
Lin, Eugene T., Gregory W. Cook, Paul Salama, & Edward J. Delp. (2002). An overview of security issues in streaming video. 88. 345–348. 15 indexed citations
13.
Khokhar, Ashfaq, Gregory W. Cook, Leah H. Jamieson, & Edward J. Delp. (2002). Coarse-grained algorithms and implementations of structural indexing-based object recognition on Intel Touchstone Delta. 279–283. 3 indexed citations
14.
Prades-Nebot, Josep, Gregory W. Cook, & Edward J. Delp. (2002). Rate control for fully fine-grained scalable video coders. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4671. 828–828. 4 indexed citations
15.
16.
Cook, Gregory W. & Edward J. Delp. (2002). The use of high performance computing in JPEG image compression. 1904. 846–851. 6 indexed citations
17.
Cook, Gregory W., et al.. (1988). Correlated Background Adaptive Clutter Suppression And Normalization Techniques. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 933. 32–32. 13 indexed citations
18.
Cook, Gregory W.. (1977). Estimation of Contrasts of Log-Frequencies. Biometrics. 33(3). 548–548. 3 indexed citations
19.
Kerridge, D. F. & Gregory W. Cook. (1976). Yet another series for the normal integral. Biometrika. 63(2). 401–407. 17 indexed citations
20.
Cook, Gregory W., et al.. (1968). Statistical music analysis: An objection to Fucks' curtosis curve (Corresp.). IEEE Transactions on Information Theory. 14(1). 152–153. 1 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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