PROCÉDÉ ET DISPOSITIF DE SEGMENTATION D'IMAGE DESTINÉS À ÊTRE UTILISÉS POUR UNE SURVEILLANCE UTILISANT DES FILTRES DE CONVOLUTION PONDÉRÉS POUR DES CELLULES DE GRILLE RESPECTIVES EN CONVERTISSANT LES MODES SELON LES CATÉGORIES DE ZONES POUR SATISFAIRE AU NIVEAU 4 DES VÉHICULES AUTONOMES, PROCÉDÉ DE TEST ET DISPOSITIF DE TEST LES UTILISANT

摘要

A method for segmenting an image by using each of a plurality of weighted convolution filters for each of grid cells to be used for converting modes according to classes of areas is provided to satisfy level 4 of an autonomous vehicle. The method includes steps of: a learning device (a) instructing (i) an encoding layer to generate an encoded feature map and (ii) a decoding layer to generate a decoded feature map; (b) if a specific decoded feature map is divided into the grid cells, instructing a weight convolution layer to set weighted convolution filters therein to correspond to the grid cells, and to apply a weight convolution operation to the specific decoded feature map; and (c) backpropagating a loss. The method is applicable to CCTV for surveillance as the neural network may have respective optimum parameters to be applied to respective regions with respective distances.