Reconstruction of Mixed Boundary Objects and Classification Using Deep Learning and Linear Sampling Method
S. B. Harisha,
E. Mallikarjun,
M. Amit
Abstract:The linear sampling method is a simple and reliable linear inversion technique for determining the morphological features of unknown objects under investigation. Nevertheless, there are many challenges that this method depends on the frequency of operation and it is unable to produce satisfactory results for objects with complex shapes. This paper proposes a hybrid model, which combines conventional linear sampling method and deep learning for the reconstruction of mixed boundary objects. In this approach, the… Show more
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