Patent ID: 11875494
Assignee: LENDBUZZ, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method comprising:
receiving, by a processor, an image that is to be analyzed for authenticity;
providing, by the processor, the image as input to a trained machine-learning model for detecting a manipulation of the image, wherein the trained machine-learning model includes:
a constrained convolutional layer that is configured to employ a filter having a set of weights with a sum of zero for detecting one or more image-manipulation fingerprints in the image and generate a feature map associated with the image-manipulation fingerprints;
a plurality of separable convolutional layers that are subsequent to the constrained convolutional layer, the plurality of separable convolution layers being configured to perform a respective spatial convolution on each color channel of the image based on the feature map to generate a plurality of feature maps corresponding to the image;
a plurality of maximum-pooling layers that are interspersed between the plurality of separable convolutional layers;
a global average-pooling layer that is subsequent to the plurality of separable convolutional layers for averaging the plurality of feature maps to generate a vector of feature values; and
a fully connected layer that is subsequent to the global average-pooling layer for receiving the vector of feature values and outputting an indication of whether the image was manipulated or not manipulated;

receiving, by the processor, the indication of whether the image was manipulated or not manipulated from the trained machine-learning model; and
outputting, by the processor and based on the indication, a classification of the image as manipulated or not manipulated for display on a display device.