Patent ID: 11908240
Assignee: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. The method according to claim 1, wherein a loss function used for training the spatiotemporal feature neural network is a cross-entropy loss function,, L
  =
  
   
    
     1
     N
    
    ⁢
    
     
      ∑
      i
     
     
      L
      i
     
    
   
   =
   
    
     1
     N
    
    ⁢
    
     
      ∑
      i
     
     
      -
      
       
        ∑
        
         c
         =
         1
        
        M
       
       
        
         y
         ic
        
        ⁢
        
         log
         ⁡
         (
         
          P
          ic
         
         )
        
       
      
     
    
   
  
 

where M is a quantity of categories; yic refers to an indicator variable, where if a current category is same as a category of an observed sample i, then yic is 1, otherwise yic is 0; Pic is a predicted probability of the observed sample i belonging to the current category; and N is a quantity of samples; and
wherein a Stochastic Gradient Descent method is used to calculate the loss function during training of the spatiotemporal feature neural network.