Patent ID: 11908118
Assignee: CITIC DICASTAL CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 2:
3. The method for analyzing images of material characterization according to claim 2, wherein the training of the said first neural network model comprises the following steps:
S1. Input a pixel matrix of any one of the first material characterization images in the said first data set into the initial neural network model, and after the pixel values are sequentially calculated through the convolutional layers, the pooling layers, the fully connected layers, and the fully convolutional layers, an output pixel matrix is obtained;
S2. Compare the said output pixel matrix obtained in step S1 with the pixel matrix of the said first material characterization image used in step S1, and calculate a loss function value;
S3. Repeat steps S1 to S2 and input the pixel matrices of the said other first material characterization images in the said first data set into the said initial neural network model to obtain corresponding loss function value related to each of the said first material characterization image; then calculate the loss gradient according to each loss function value, and use a chain method to adjust network parameters in the said initial neural network model to obtain an adjusted neural network model;
S4. Replace the said initial neural network model with the said adjusted neural network model, and repeat steps S1 to S3 to adjust the said network parameters until the obtained loss function value is within a predetermined threshold range, thus finishing the training of the first neural network model.