David Chelberg

783 total citations
67 papers, 515 citations indexed

About

David Chelberg is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, David Chelberg has authored 67 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Vision and Pattern Recognition, 11 papers in Computational Mechanics and 9 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in David Chelberg's work include Medical Image Segmentation Techniques (9 papers), Computer Graphics and Visualization Techniques (9 papers) and Advanced Image and Video Retrieval Techniques (9 papers). David Chelberg is often cited by papers focused on Medical Image Segmentation Techniques (9 papers), Computer Graphics and Visualization Techniques (9 papers) and Advanced Image and Video Retrieval Techniques (9 papers). David Chelberg collaborates with scholars based in United States, South Korea and Germany. David Chelberg's co-authors include Jean Ponce, Peter Henstock, Zygmunt Pizlo, Jason C. Hsu, Charles F. Babbs, Edward J. Delp, Limin Ma, Mehmet Çelenk, Juneho Yi and Teresa Franklin and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

David Chelberg

64 papers receiving 475 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Chelberg United States 12 313 84 70 60 56 67 515
Jan Fischer Germany 14 379 1.2× 147 1.8× 59 0.8× 34 0.6× 69 1.2× 53 567
Masatsugu Kidode Japan 12 300 1.0× 68 0.8× 52 0.7× 40 0.7× 33 0.6× 66 453
Seungkyu Lee South Korea 13 486 1.6× 114 1.4× 26 0.4× 82 1.4× 35 0.6× 63 687
Masahiko Yachida Japan 13 490 1.6× 166 2.0× 62 0.9× 109 1.8× 23 0.4× 98 632
Donald Hearn United States 4 195 0.6× 32 0.4× 41 0.6× 18 0.3× 72 1.3× 9 382
Aladine Chetouani France 16 448 1.4× 51 0.6× 39 0.6× 138 2.3× 63 1.1× 89 741
German Cheung United States 7 585 1.9× 112 1.3× 74 1.1× 34 0.6× 79 1.4× 8 809
M. Pauline Baker United States 4 195 0.6× 31 0.4× 41 0.6× 18 0.3× 69 1.2× 8 378
Louise Stark United States 11 268 0.9× 132 1.6× 90 1.3× 18 0.3× 16 0.3× 39 407

Countries citing papers authored by David Chelberg

Since Specialization
Citations

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

Fields of papers citing papers by David Chelberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Chelberg

This figure shows the co-authorship network connecting the top 25 collaborators of David Chelberg. A scholar is included among the top collaborators of David Chelberg 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 David Chelberg. David Chelberg 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.
Chelberg, David, et al.. (2009). Using the Virtual World of Second Life to Create Educational Games for Real World Middle School Science Classrooms. EdMedia: World Conference on Educational Media and Technology. 2009(1). 2124–2133. 5 indexed citations
2.
Liu, Chang, et al.. (2009). Weather Challenge: A Case Study in Using Second Life to Create Educational Science Games for Middle School Classrooms. Society for Information Technology & Teacher Education International Conference. 2009(1). 1422–1429. 3 indexed citations
3.
Franklin, Teresa, Gene A. Tagliarini, Gerald Knezek, et al.. (2009). STEM Learning in Middle School with Games and Simulations. Society for Information Technology & Teacher Education International Conference. 2009(1). 1445–1449. 1 indexed citations
4.
Chelberg, David, et al.. (2009). An Overview of First Generation STEAMiE Learning Objects. EdMedia: World Conference on Educational Media and Technology. 2009(1). 3748–3757. 2 indexed citations
5.
Young, William A., et al.. (2009). An Investigation of Self-Efficacy using Educational Video Games Developed by the GK-12 STEAM Project. Society for Information Technology & Teacher Education International Conference. 2009(1). 3695–3707. 2 indexed citations
6.
Zhou, Qiang, Limin Ma, Mehmet Çelenk, & David Chelberg. (2005). Content-Based Image Retrieval Based on ROI Detection and Relevance Feedback. Multimedia Tools and Applications. 27(2). 251–281. 20 indexed citations
7.
Ponce, Jean & David Chelberg. (2005). Localized intersections computation for solid modelling with straight homogenous generalized cylinders. 4. 1481–1486. 2 indexed citations
8.
Zhou, Qiang, Limin Ma, & David Chelberg. (2005). Adaptive object detection and recognition based on a feedback strategy. Image and Vision Computing. 24(1). 80–93. 5 indexed citations
9.
Watson, Daniel W., et al.. (2003). A parallel approach to hybrid range image segmentation. 334–342. 1 indexed citations
10.
Andrews, David, et al.. (2002). A Framework for using benefit functions in complex real-time systems. Scalable Computing Practice and Experience. 5(1). 2 indexed citations
11.
Hsu, Jason C., David Chelberg, & Charles F. Babbs. (2002). A geometric modeling tool for visualization of human anatomical structures. 14. 176–183.
12.
Pizlo, Zygmunt, et al.. (1999). Binocular Shape Reconstruction: Psychological Plausibility of the 8-Point Algorithm. Computer Vision and Image Understanding. 74(2). 121–137. 10 indexed citations
13.
Watson, Daniel W., et al.. (1999). Aspects of computational mode and data distribution for parallel range image segmentation. Parallel Computing. 25(5). 499–523. 2 indexed citations
14.
Henstock, Peter & David Chelberg. (1996). Automatic gradient threshold determination for edge detection. IEEE Transactions on Image Processing. 5(5). 784–787. 45 indexed citations
15.
Hsu, Jason C., David Chelberg, Charles F. Babbs, Zygmunt Pizlo, & Edward J. Delp. (1995). Preclinical ROC studies of digital stereomammography. IEEE Transactions on Medical Imaging. 14(2). 318–327. 29 indexed citations
16.
Pizlo, Zygmunt, et al.. (1994). Design of Studies to Test the Effectiveness of Stereo Imaging Truth or Dare: Is Stereo Viewing Really Better?. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2177. 211–222. 2 indexed citations
17.
Hsu, Jason C. & David Chelberg. (1994). Visible Light and X-Ray Ray Tracing of Generalized Cylinders. 56(5). 392–401. 6 indexed citations
18.
Chelberg, David & Juneho Yi. (1992). <title>Range image segmentation using regularization</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1607. 336–347. 2 indexed citations
19.
Ponce, Jean & David Chelberg. (1988). Finding the limbs and cusps of generalized cylinders. International Journal of Computer Vision. 1(3). 195–210. 38 indexed citations
20.
Levitt, Tod S., Daryl T. Lawton, David Chelberg, & Philip Nelson. (1987). Qualitatne landmark-based path planning and following. National Conference on Artificial Intelligence. 689–694. 19 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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