Patent ID: 11875597
Assignee: IDENTY INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. The method of claim 9, wherein each depthwise convolutional layer of the neural network applies a predefined kernel K to the matrix I, the predefined kernel K being a matrix of size S×T where S, T<N; S, T<M comprising entries Sab, wherein applying the kernel to the matrix comprises calculating an inner product of the predefined kernel K with each reduced matrix R of size (N×M)S,T of a matrix Z, where the matrix R has the same size as the predefined kernel K, and the matrix Z has size (N+2Pw)×(M+2Ph) and the entries of the matrix Zcd with c, d∈+ are given by, Z
    cd
  
  =
  
    {
    
      
        
          
            0
            ⁢
            
              ∀
              
                c
                ≤
                
                  P
                  w
                
              
            
          
        
      
      
        
          
            0
            ⁢
            
              ∀
              
                c
                >
                
                  
                    P
                    w
                  
                  +
                  N
                
              
            
          
        
      
      
        
          
            0
            ⁢
            
              ∀
              
                d
                ≤
                
                  P
                  h
                
              
            
          
        
      
      
        
          
            0
            ⁢
            
              ∀
              
                d
                >
                
                  
                    P
                    h
                  
                  +
                  M
                
              
            
          
        
      
      
        
          
            
              
                
                  I
                  
                    i
                    ⁢
                    j
                  
                
                ⁢
                
                  
                
                ⁢
                where
                ⁢
                
                  
                
                ⁢
                c
              
              =
              
                i
                +
                
                  P
                  w
                
              
            
            ;
            
              d
              =
              
                j
                +
                
                  P
                  h
                
              
            
            ;
            
              i
              =
              
                1
                ⁢
                
                  
                
                ⁢
                …
                ⁢
                
                  
                
                ⁢
                N
              
            
            ;
            
              j
              =
              
                1
                ⁢
                
                  
                
                ⁢
                …
                ⁢
                
                  
                
                ⁢
                M, and provide a matrix P as output, wherein the matrix P has the size (N−S+2Pw/Ww+1)×(M−T+2Ph/Wh+1), where Ww and Wh define stride width and each entry Pij of the matrix P is a value of the inner product of the ij-th reduced matrix R with the kernel K, wherein the matrix P is provided as output by the depthwise convolutional layer to a first batch normalizer of the neural network.