David Casasent

8.2k citations
498 papers · 5.6k · h-index 33

Impact in

Papers in

David Casasent

460 papers receiving 5.3k citations

Peers

David Casasent
Comparison fields: 5 of 148
  • Media Technology 2.0k
  • Computer Vision and Pattern Recognition 2.1k
  • Signal Processing 448
  • Atomic and Molecular Physics, and Optics 1.1k
  • Artificial Intelligence 1.1k
Replace B. V. K. Vijaya Kumar with:
B. V. K. Vijaya Kumar United States
Gonzalo R. Arce United States
Edmund Y. Lam Hong Kong
Hua Huang China
Neal C. Gallagher United States
José L. Marroquín Mexico
Seong G. Kong South Korea
Harold Szu United States
Yaakov Weiss Israel
David Martín Spain
David Casasent relative to B. V. K. Vijaya Kumar United States B. V. K. Vijaya Kumar's profile →
Citations per field
00.5×1.5×
B. V. K. Vijaya Kumar · 1×
Citations per year

Countries citing papers authored by David Casasent

Since Specialization
Citations

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

Fields of papers citing papers by David Casasent

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Casasent, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Casasent Line = papers co-authored together David Casasent links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 498 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987405
2 1976381
3 1980261
4 1984208
5 1977134
6 200898
7 198696
8 197790
9 197981
10 199271
11 197668
12 199762
13 198755
14 200352
15 199152
16 197951
17 198950
18 198947
19 199247
20 200745

About David Casasent

David Casasent is a scholar working on Electrical and Electronic Engineering, Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 498 papers that have together received 5.6k indexed citations. Recurring topics across this work include Photonic and Optical Devices (104 papers), Advanced Optical Imaging Technologies (79 papers), Neural Networks and Applications (72 papers), Infrared Target Detection Methodologies (67 papers), Optical Network Technologies (56 papers), Semiconductor Lasers and Optical Devices (54 papers), Optical and Acousto-Optic Technologies (54 papers) and Remote-Sensing Image Classification (48 papers). The work is most often cited by research in Media Technology (2.0k citations), Computer Vision and Pattern Recognition (2.1k citations), Signal Processing (448 citations), Atomic and Molecular Physics, and Optics (1.1k citations) and Artificial Intelligence (1.1k citations). David Casasent has collaborated with scholars based in United States, Moldova and Thailand. Frequent co-authors include Demetri Psaltis, B. V. K. Vijaya Kumar, Abhijit Mahalanobis, Songyot Nakariyakul, Charles F. Hester, Etienne Barnard, Gopalan Ravichandran, Brian A. Telfer, James R. Jackson and Ashit Talukder. Their work appears in journals such as Optical Engineering, Optics Communications, Neural Networks, Proceedings of the IEEE and Optics Letters.

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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