Nneten2d: two-dimensional neural network entropy in remote sensing imagery and geophysical mapping

HIGHLIGHTS

• who: Andrei Velichko et al. from the Institute of Physics and Technology, Petrozavodsk State University, Petrozavodsk, Russia have published the Article: NNetEn2D: Two-Dimensional Neural Network Entropy in Remote Sensing Imagery and Geophysical Mapping, in the Journal: (JOURNAL) of 30/04/2022
• what: To overcome these difficulties this study proposes a new method for estimating two-dimensional neural network entropy (NNetEn2D ) for evaluating the regularity or predictability of images using the LogNNet neural network model. The authors demonstrate the advantage of using circular instead of square kernels through comparison of the invariance of the NNetEn2D . . .
  

   

  

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