Systems and Methods for Model Training Based on Feature Fusion of Multiple Data Types

A method comprising:

• receiving, by one or more processing circuits, a plurality of first data elements of a first data type and a plurality of second data elements of a second data type, wherein the first data type is text data and the second data type is at least one of image data or video data;
• identifying, by the one or more processing circuits, first features of each of the plurality of first data elements;
• identifying, by the one or more processing circuits, second features of each of the plurality of second data elements;
• generating, by the one or more processing circuits, merged features by combining a first feature of the first features of each of the plurality of first data elements with a second feature of the second features of one of the plurality of second data elements, wherein the first feature and the second feature each represent a common feature;
• and
• generating, by the one or more processing circuits, a model based on the common features and at least a portion of the first features and the second features.