State Farm Mutual Automobile Insurance Company

Jing Wan

Rajiv C Shah

Ronald R Duehr

Lucas Allen

Jeffrey David Hevrin

Taylor Griffin Smith

Sripriya Sundararaman

Jeremy Cunningham

Shannon Morrison

Brad Sliz

Marigona Bokshi-Drotar

Yuntao Li

Sandra Kane

Charlie Isaksson

Systems and methods for analyzing image data to assess property damage are disclosed. According to certain aspects, a server may analyze segmented digital image data of a roof of a property using a convolutional neural network (CNN). The server may extract a set of features from a set of regions output by the CNN. Additionally, the server may analyze the set of features using an additional image model to generate a set of outputs indicative of a confidence level that actual hail damage is depicted in the set of regions.

Technologies for using image data analysis to assess and classify hail damage

A computer-implemented method for determining features of a dataset that are indicative of anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) executing a time series decomposition algorithm on a portion of the features of the data to generate a first list of features, (3) implementing a plurality of traffic dispersion graphs to generate a second list of features, and (4) implementing an autoencoder and a random forest regressor to generate a third list of features.

Detection of anomalous computer behavior

A computer-implemented method for detecting anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) applying a first plurality of algorithms to determine features of the data which may contribute to anomalous behavior of the computers, and (3) applying a second plurality of algorithms to determine which computers are behaving anomalously based upon the features.

An image analysis ('IA') computer system for analyzing images of hail damage includes at least one processor in communication with at least one memory device. The at least one processor is programmed to: (i) store a damage prediction model associated with a rooftop, wherein the damage prediction model utilizes an artificial intelligence algorithm; (ii) display, to a user, an image of a rooftop; (iii) receive, from the user, a request to analyze damage to the rooftop; (iv) apply, by the at least one processor, the damage prediction model to the image, the damage prediction model outputting a plurality of damage prediction locations of the rooftop in relation to the image; and/or (v) display, by the at least one processor, an overlay box at each of the plurality of damage prediction locations, the overlay box being a virtual object overlaid onto the image for labeling the damage prediction locations.

Systems and methods for image labeling using artificial intelligence

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Allen, TX, United States of America

Jing Wan