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An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs

Overview of attention for article published in Frontiers in Neuroinformatics, January 2013
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Title
An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs
Published in
Frontiers in Neuroinformatics, January 2013
DOI 10.3389/fninf.2013.00035
Pubmed ID
Authors

Kishore R. Mosaliganti, Arnaud Gelas, Sean G. Megason

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Greece 1 2%
China 1 2%
France 1 2%
Unknown 41 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 27%
Researcher 6 13%
Student > Bachelor 4 9%
Student > Master 4 9%
Professor > Associate Professor 3 7%
Other 9 20%
Unknown 7 16%
Readers by discipline Count As %
Engineering 10 22%
Computer Science 10 22%
Agricultural and Biological Sciences 7 16%
Nursing and Health Professions 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 7 16%
Unknown 7 16%