Dc Burr

724 total citations
13 papers, 533 citations indexed

About

Dc Burr is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Dc Burr has authored 13 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 4 papers in Signal Processing and 4 papers in Artificial Intelligence. Recurrent topics in Dc Burr's work include Music and Audio Processing (4 papers), Neural Networks and Applications (3 papers) and Handwritten Text Recognition Techniques (2 papers). Dc Burr is often cited by papers focused on Music and Audio Processing (4 papers), Neural Networks and Applications (3 papers) and Handwritten Text Recognition Techniques (2 papers). Dc Burr collaborates with scholars based in United States and Japan. Dc Burr's co-authors include R. T. Chien, B. Ackland, Neil Weste, Robyn Owens, Joshua V. Ross, Maria Concetta Morrone, Arezoo Pooresmaeili and Paola Binda and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Investigative Ophthalmology & Visual Science and Perception.

In The Last Decade

Dc Burr

13 papers receiving 489 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dc Burr United States 7 321 202 84 35 34 13 533
Matthew D. Mullin United States 9 496 1.5× 152 0.8× 62 0.7× 43 1.2× 22 0.6× 11 657
Αλεξάνδρα Ψαρρού United Kingdom 11 448 1.4× 118 0.6× 84 1.0× 30 0.9× 28 0.8× 55 608
G. Scott United Kingdom 7 370 1.2× 76 0.4× 58 0.7× 105 3.0× 51 1.5× 13 478
Shoou-I Yu United States 17 691 2.2× 316 1.6× 75 0.9× 27 0.8× 62 1.8× 31 891
Song-Chun Zhu United States 5 671 2.1× 233 1.2× 41 0.5× 49 1.4× 37 1.1× 8 804
J. Ben-Arie United States 14 597 1.9× 107 0.5× 65 0.8× 78 2.2× 58 1.7× 76 741
Song-Chun Zhu United States 5 468 1.5× 73 0.4× 63 0.8× 27 0.8× 57 1.7× 7 542
Jonathan K. Su United States 11 420 1.3× 190 0.9× 63 0.8× 39 1.1× 13 0.4× 16 629
Bilge Günsel Türkiye 19 713 2.2× 146 0.7× 349 4.2× 48 1.4× 45 1.3× 89 978
Farhad Kamangar United States 10 321 1.0× 171 0.8× 66 0.8× 48 1.4× 26 0.8× 48 608

Countries citing papers authored by Dc Burr

Since Specialization
Citations

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

Fields of papers citing papers by Dc Burr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dc Burr

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

All Works

13 of 13 papers shown
1.
Pooresmaeili, Arezoo, et al.. (2010). 'Non-retinotopic processing' in Ternus motion displays modelled by spatiotemporal filters. Perception. 39. 94–94. 1 indexed citations
2.
Binda, Paola, Dc Burr, & Maria Concetta Morrone. (2007). Spatio-temporal distortions of visual perception during saccades. CINECA IRIS Institutial research information system (University of Pisa). 36. 112–112. 1 indexed citations
3.
Burr, Dc, et al.. (2002). Hierarchical recurrent networks for learning musical structure. 216–225. 1 indexed citations
4.
Burr, Dc & Maria Concetta Morrone. (1992). TEMPORAL IMPULSE-RESPONSE FUNCTIONS FOR LUMINANCE AND COLOR. Investigative Ophthalmology & Visual Science. 33(4). 955–955. 2 indexed citations
5.
6.
Morrone, Maria Concetta, et al.. (1992). A VISUAL MODEL FOR SIMULTANEOUS ANALYSIS OF FORM AND MOTION. CINECA IRIS Institutial research information system (University of Pisa). 33(4). 973–973. 1 indexed citations
7.
Burr, Dc. (1988). Experiments on neural net recognition of spoken and written text. IEEE Transactions on Acoustics Speech and Signal Processing. 36(7). 1162–1168. 196 indexed citations
8.
Ross, Joshua V., et al.. (1986). MACH BANDS DEPEND ON VISUAL PHASE. Perception. 15. 6 indexed citations
9.
Burr, Dc. (1983). Designing a Handwriting Reader. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-5(5). 554–559. 46 indexed citations
10.
Burr, Dc. (1981). Elastic Matching of Line Drawings. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-3(6). 708–713. 136 indexed citations
11.
Ackland, B., Neil Weste, & Dc Burr. (1981). An integrated multiprocessing array for time warp pattern matching. 197–215. 16 indexed citations
12.
Burr, Dc. (1981). A dynamic model for image registration. Computer Graphics and Image Processing. 15(2). 102–112. 110 indexed citations
13.
Burr, Dc & R. T. Chien. (1977). A system for stereo computer vision with geometric models. International Joint Conference on Artificial Intelligence. 31(41). 583–583. 13 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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