Patent ID: 11934790
Assignee: BOE TECHNOLOGY GROUP CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 12:
13. The training method according to claim 9, wherein the system loss function is expressed as:

Lobj=λ1·L(Y1,T1)+λ2·L(Y2,T2)

wherein Lobj represents the system loss function, L(⋅, ⋅) represents a cross entropy loss function, Y1 represents the predicted class label of the first training remark, T1 represents a true class label of the first training remark, L(Y1,T1) represents a cross entropy loss function of the first training remark, X represents a weight of the cross entropy loss function L(Y1,T1) of the first training remark in the system loss function, Y2 represents the predicted class label of the second training remark, T1 represents a true class label of the second training remark, L(Y2,T2) represents a cross entropy loss function of the second training remark, X2 represents a weight of the cross entropy loss function L(Y2,T2) of the second training remark in the system loss function;
the cross entropy loss function L(⋅, ⋅) is expressed as:, L
   ⁡
   (
   
    Y
    ,
    T
   
   )
  
  =
  
   -
   
    
     ∑
     
      i
      =
      1
     
     N
    
    
     
      ∑
      
       j
       =
       1
      
      K
     
     
      
       Y
       i
       j
      
      ⁢
      log
      ⁢
      
       (
       
        T
        i
        j
       
       )
      
     
    
   
  
 

wherein Y and T are formal parameters, N represents a number of training remarks, K represents a number of class labels of semantic classification, Yij represents a probability value of a j-th class label in predicted class labels of an i-th training remark, and Tij represents a probability value of a j-th class label in true class labels of an i-th training remark.