Richard E. Woods

20 papers receiving 5.6k citations

Hit Papers

Digital image processing using MATLAB200920262014202020092009201410002.0k3.0k4.0k

Peers

Richard E. Woods
Comparison fields: 5 of 201
  • Computer Vision and Pattern Recognition 2.9k
  • Media Technology 998
  • Artificial Intelligence 667
  • Radiology, Nuclear Medicine and Imaging 542
  • Biomedical Engineering 524
Replace Stephen M. Pizer with:
Stephen M. Pizer United States
Linda G. Shapiro United States
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Richard E. Woods relative to Stephen M. Pizer United States Stephen M. Pizer's profile →
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Countries citing papers authored by Richard E. Woods

Since Specialization
Citations

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

Fields of papers citing papers by Richard E. Woods

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard E. Woods. 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 Richard E. Woods. The network helps show where Richard E. Woods may publish in the future.

Co-authorship network of co-authors of Richard E. Woods

This figure shows the co-authorship network connecting the top 25 collaborators of Richard E. Woods. A scholar is included among the top collaborators of Richard E. Woods 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 Richard E. Woods. Richard E. Woods 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
#WorkIndexed citations
1
Digital Image Processing 3rd Editionbreakdown →
395
2
Digital image processing using MATLABbreakdown →
4544
3
Digital Image Processing Using MATLAB: AND Mathworks, MATLAB Sim SV 07
26
4 68
5
Digital Image Processing Using Matlab tm
7
6 20
7 25
8 43
9
Trait variability and stress: canalization, developmental stability and the need for a broad approach
34
10 22
11 50
12 3
13 113
14 26
15 47
16 2
17 22
18 2
19 31
20
Digital Image Processing, 4Th Edition
15

About Richard E. Woods

Richard E. Woods is a scholar working on Geometry and Topology, Aging and Nature and Landscape Conservation, having authored 21 papers that have together received 6.3k indexed citations. Recurring topics across this work include Morphological variations and asymmetry (10 papers), Animal Ecology and Behavior Studies (2 papers) and Ecology and Vegetation Dynamics Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.9k citations), Media Technology (998 citations) and Geometry and Topology (333 citations). Richard E. Woods has collaborated with scholars based in Australia, United States and Portugal. Frequent co-authors include Rafael C. González, S.L. Eddins, Barry R. Masters, Ary A. Hoffmann, Miriam J. Hercus, Carla M. Sgrò, R. C. Gonzalez, John A. McKenzie, Michael P. Schwarz and Philip Batterham. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the IEEE and The American Naturalist.

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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