Fig. 3
(a) During the training of the BPI-CA, the three-layered template of nine cells per layer is moved across the ROIs channels of the wound images of the training set. At each epoch the template is moved by one pixel and takes in input the values of the of the R, G and B channels which serve as coordinates for the memristive cells in tensor \({\textbf {O}}\). (b) Similarly after training (i.e. when the value of the cells in tensor \({\textbf {O}}\) have been fixed) the template is moved across the ROI in which the wound is framed in the picture. Each layer of the template takes into account one of the digital channels of the photo and the single pixel values serve as coordinates of the given cell of the tensor. At this stage it is possible to recognize a sub-space \(\Omega \in {\textbf {O}}\) in which are encoded the extracted color feature of the analysed wounds.
