Abstract: The present disclosure provides a method of facilitating authenticating of users. Further, the method includes initiating, using a processing device, an authentication session for a user for an authentication instance. Further, the method includes identifying, using the processing device, authentication prompts for the authenticating of the user based on the initiating. Further, the method includes transmitting, using a communication device, the authentication prompts to user devices. Further, the method includes receiving, using the communication device, data in response to the authentication prompts from the user devices. Further, the method includes analyzing, using the processing device, the data using machine learning models. Further, the method includes generating, using the processing device, an authentication status for the user based on the analyzing. Further, the method includes terminating, using the processing device, the authentication session based on the generating.

Abstract: A computer implemented method for generating synthetic training data to train a convolutional neural network is described. The method consists of steps including receiving a source image depicting an object for identification. The type and shape of the depicted object is determined. The source image is overlayed with a N×M grid of vertices, the grid including horizontal and vertical edges and being fit to the shape of the depicted object. For each vertex in the grid, perturbations are added to the (x,y) coordinates of the vertex and the pixel values in a range between the original and final (x,y) coordinates are interpolated, resulting in the generation of an item of synthetic training data. The method is repeated to generate multiple items of synthetic training data which are then used to train a neural network to identify the object in an image.

Abstract: A computer implemented method for generating synthetic training data to train a convolutional neural network is described. The method consists of steps including receiving a source image depicting an object for identification. The type and shape of the depicted object is determined. The source image is overlayed with a N×M grid of vertices, the grid including horizontal and vertical edges and being fit to the shape of the depicted object. For each vertex in the grid, perturbations are added to the (x,y) coordinates of the vertex and the pixel values in a range between the original and final (x,y) coordinates are interpolated, resulting in the generation of an item of synthetic training data. The method is repeated to generate multiple items of synthetic training data which are then used to train a neural network to identify the object in an image.