Patent ID: 11966670
Assignee: TERRAFUSE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. The method of claim 1, wherein the one or more probabilistic mapping function emulators returns a probability for the value of the ground truth, wherein the one or more probabilistic mapping function emulators comprises a series of tensor operations with weights representing a set of spatial filters that include convolutional filters, and a set of down-sampling and up-sampling layers and nonlinear operations; and
wherein training the model comprises calculating an optimal version of the weights of the set of spatial filters, comprising:
a) beginning with random initial weights, first calculating an estimated value for the mask by executing the series of tensor operations with the random initial weights and then determining a value of a loss function which represents an error between the estimated value and the value of the ground truth of the mask;
b) minimizing the loss function by calculating gradients of the loss function with respect to the random initial weights and then iteratively updating the weights to successive intermediate versions of the weights and re-calculating the value of the loss function and its gradients with each iteration until the loss function has been reduced to a satisfactory minimum value, at which point the optimal version of the weights are set to a most recent intermediate version of the weights.