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We analyze the performance of the Huber regularizer in the application, studying the influence of the parameters under different noise levels. Moreover, we ...
We analyze the performance of the Huber regularizer in the application, studying the influence of the parameters under different noise levels. Moreover, we ...
The Huber function is known to yield robust estimations reducing the effect of outliers. We introduced previously a regularization approach for quantitative ...
We analyze the performance of the Huber regularizer in the application, studying the influence of the parameters under different noise levels. Moreover, we ...
In this paper, we employ the Huber function as regularization in a challenging inverse problem: quantitative microwave imaging. Quantitative microwave ...
In this paper, we employ the Huber function as regularization in the even more challenging 3D piecewise continuous case of a realistic numerical breast phantom.
Quantitative active microwave imaging for breast cancer screening and therapy monitoring applications requires adequate reconstruction algorithms, ...
We present an analysis of weakly convex discontinuity adaptive (WCDA) models for regularizing three-dimensional (3D) quantitative microwave ima-.
The paper presents an overview of the soft prior algorithm and describes how the synthetic microwave data was generated from image data obtained from the ...
Missing: sparsely | Show results with:sparsely
The hybrid method performs better in terms of speed and memory use on large sparse configurations than both the FFT method and the HF MLFMA separately and it ...