Dan E. Dudgeon
About
In The Last Decade
Dan E. Dudgeon
37 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Signal Processing 1.3k
- Aerospace Engineering 646
- Computational Mechanics 635
- Computer Vision and Pattern Recognition 620
- Electrical and Electronic Engineering 473
Countries citing papers authored by Dan E. Dudgeon
This map shows the geographic impact of Dan E. Dudgeon'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 Dan E. Dudgeon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan E. Dudgeon more than expected).
Fields of papers citing papers by Dan E. Dudgeon
This network shows the impact of papers produced by Dan E. Dudgeon. 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 Dan E. Dudgeon. The network helps show where Dan E. Dudgeon may publish in the future.
Co-authorship network of co-authors of Dan E. Dudgeon
This figure shows the co-authorship network connecting the top 25 collaborators of Dan E. Dudgeon. A scholar is included among the top collaborators of Dan E. Dudgeon 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 Dan E. Dudgeon. Dan E. Dudgeon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | Model-Based Automatic Target Recognition Sys- tem for the UGV/RSTA Ladar: Status at Demo C | 2 |
| 6 | Progress Report on the Development of the Automatic Target Recognition System for the UGV/RSTA LADAR | 2 |
| 7 | 31 | |
| 8 | Pixel-Level Fusion Using 'Interest' Images | 10 |
| 9 | Machine Intelligent Automatic Recognition of Critical Mobile Targets in Laser Radar Imagery | 11 |
| 10 | Array Signal Processing: Concepts and Techniques breakdown → | 1430 |
| 11 | Functional Templates and Their Applications to 3-D Object Recognition | 3 |
| 12 | 3 | |
| 13 | Machine Intelligence Technology for Automatic Target Recognition | 18 |
| 14 | Automatic Object Recognition from Range Imagery Using Appearance Models | 6 |
| 15 | Feature Extraction in Laser-radar Range Imagery: I. Contour-based Approach | 1 |
| 16 | Feature Extraction in Laser-radar Range Imagery: II. Intensity-Cued Region-based Approach | 1 |
| 17 | Silhouette Understanding System for Laser-radar Range Imagery | 1 |
| 18 | Multidimensional digital signal processing breakdown → | 773 |
| 19 | 9 | |
| 20 | 22 |
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.