HIGHLIGHTS
- who: DnCNN et al. from the , Le Mans, France have published the paper: Imaging Deep Learning Network for Speckle De-Noising in, in the Journal: (JOURNAL) of 15/04/2022
- what: In the present paper, networks are evaluated in terms of phase errors and generalization power defined as the "ability to perform well on previously unobserved inputs" . To evaluate the efficiency of iterations of the Pythorch model, the authors compare three versions which are called DL_DB128, DL_DB128_2 and DL_DB128_3. DLSHIFT algorithm achieved no better phase error than 0.16 rad due to the fact that . . .
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