Patent ID: 11922290
Assignee: VISA INTERNATIONAL SERVICE ASSOCIATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. The method of claim 7, wherein the input to the dual-attention component of the machine learning model comprises a real input portion and an imaginary input portion,
wherein the real input portion comprises:
a first real input based on an output of the one-dimensional feature extraction convolutional layer for the combined real part of the first plurality of features;
a second real input based on an output of the one-dimensional feature extraction convolutional layer for the combined real part of the second plurality of features; and
a third real input based on an output of the one-dimensional feature extraction convolutional layer for the combined real part of the third plurality of features; and

wherein the imaginary input portion comprises:
a first imaginary input based on an output of the one-dimensional feature extraction convolutional layer for the combined imaginary part of the first plurality of features;
a second imaginary input based on an output of the one-dimensional feature extraction convolutional layer for the combined imaginary part of the second plurality of features; and
a third imaginary input based on an output of the one-dimensional feature extraction convolutional layer for the combined imaginary part of the third plurality of features; and

wherein training the machine learning model comprises:
generating a real component attention matrix based on the real input portion, wherein the real component attention matrix has a number of attention vectors that is equal to a number of features of the plurality of transaction features; and
generating an imaginary component attention matrix based on the imaginary input portion, wherein the imaginary component attention matrix has a number of attention vectors that is equal to a number of features of the plurality of transaction features.