Levenberg–Marquardt level set methods for inverse obstacle problems
By Martin Burger. 2004
68 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/2cca4e7368b12358d64280d8ab046474ea31996b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- A. Constantinescu
- Marc Bonnet
- Stanley J. Osher
- Eric T. Chung
- Xuecheng Tai
- Tony F. Chan
- Martin Burger
- Peter Richtárik
In Computer Vision and Pattern Recognition
- Xuecheng Tai
- Stanley J. Osher
- Tony F. Chan
- Martin Burger
- Eric T. Chung
- A. Constantinescu
- Marc Bonnet
- Wotao Yin
Citations in the corpus
- Inverse problems in elasticity (2005, methodology): “For completeness, it is also important to mention techniques based on level set methods, not addressed in this review, whose implementation also involves shape sensitivity concepts [18, 34, 124].”
- Electrical impedance tomography using level set representation and total variational regularization (2005, methodology): “In [5, 7, 6, 18] for some other algorithms in using level set methods for some inverse problems.”
- A survey on level set methods for inverse problems and optimal design (2005, methodology): “The efficient solution of this linear system for the model problems 1 and 3 has been investigated in Burger [26] using an all-at-once approach [29, 30, 65, 66], which leads to a large, sparse indefinite linear system for the velocity, a linearized state variable and a dual variable.”