DEEP LEARNING ARTIFICIAL INTELLIGENCE FOR OBJECT CLASSIFICATION

• US 20200134734A1
• Filed: 10/28/2019
• Published: 04/30/2020
• Est. Priority Date: 10/26/2018
• Status: Abandoned Application

• Current Assignee: Cover Financial, Inc.
• Original Assignee: Cover Financial, Inc.
• Inventors: Aneesh, Ben
• Application Number:
  US16/666,357
• Publication Number:
  US 20200134734A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06F 18/241 relating to the classification model, e.g. parametric or non-parametric approaches
• CPC Class Codes: G06F 18/24133 Distances to prototypes
• CPC Class Codes: G06N 20/20 Ensemble learning
• CPC Class Codes: G06N 3/04 Architecture, e.g. interconnection topology
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0278 Product appraisal
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/82 using neural networks
• CPC Class Codes: G06V 20/46 Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata

Abstract

Methods and system for cataloging items and classifying items are disclosed. In some embodiments, a mobile computing device may be used to capture an image of an item. The item may be identified and classified by the mobile computing device based on the image of the item. A location of the mobile computing device may be determined and associated with the image of the item.

Claims

1. A method for applied artificial intelligence object detection, comprising:

capturing, with a mobile computing device, an image of an item;

identifying, by a neural network, a classification of the item, the neural network including a plurality of convolutional filters;

recording a location of the mobile computing device;

associating the location of the mobile computing device with the image of the item; and

transmitting, from the mobile computing device and to a computing platform, the image of the item, the classification of the item, and the location of the mobile computing device,

wherein transmitting, from the mobile computing device and to the computing platform, the image of the item, the classification of the item, and the location of the mobile computing device causes the computing platform to store the image of the item, the classification of the item, and the location of the mobile computing device in a database and determine a parameter of an insurance policy based at least in part on the image of the item, the classification of the item, or the location of the mobile computing device.

2. The method of claim 1, wherein the image of the item is a frame of a video, and wherein the video comprises a plurality of frames of video.

3. The method of claim 2, further comprising:

identifying a classification of a plurality of items in the plurality of frames of video.

4. The method of claim 3, further comprising:

recording a timestamp of each frame of the video containing an item.

5. The method of claim 4, further comprising:

transmitting the classification of the plurality of items and the video to the computing platform.

6. The method of claim 1, wherein the identifying, by the mobile computing device and based on the image of the item, a classification of the item comprises:

transmitting the image of the item to an image recognition server; and

receiving, by the mobile computing device and from the image recognition server, a classification of the item.

7. The method of claim 1, wherein the identifying, by the mobile computing device and based on the image of the item, a classification of the item comprises:

processing, by the mobile computing device, the image of the item with a neural network, the neural network trained to classify images of items.

8. A non-transitory computer-readable medium containing instructions for cataloging items, the non-transitory computer-readable medium comprising instructions for:

capturing, with a mobile computing device, an image of an item;

identifying, by the mobile computing device and based on the image of the item, a classification of the item;

recording a location of the mobile computing device;

associating the location of the mobile computing device with the image of the item; and

transmitting, from the mobile computing device and to an insurance underwriting platform, the image of the item, the classification of the item, and the location of the mobile computing device,

wherein transmitting, from the mobile computing device and to the insurance underwriting platform, the image of the item, the classification of the item, and the location of the mobile computing device causes the insurance underwriting platform to store the image of the item, the classification of the item, and the location of the mobile computing device in a database and determine a parameter of an insurance policy based at least in part on the image of the item, the classification of the item, or the location of the mobile computing device.

9. The non-transitory computer-readable medium of claim 8, wherein the image of the item is a frame of a video, and wherein the video comprises a plurality of frames of video.

10. The non-transitory computer-readable medium containing instructions for cataloging items for insurance purposes of claim 9, wherein the non-transitory computer-readable medium further comprises instructions for:

identifying a classification of a plurality of items in the plurality of frames of video.

11. The non-transitory computer-readable medium containing instructions for cataloging items for insurance purposes of claim 10, wherein the non-transitory computer-readable medium further comprises instructions for:

recording a timestamp of each frame of the video containing an item.

12. The non-transitory computer-readable medium containing instructions for cataloging items for insurance purposes of claim 11, wherein the non-transitory computer-readable medium further comprises instructions for:

transmitting the classification of the plurality of items and the video to the insurance underwriting platform.

13. The non-transitory computer-readable medium of claim 8, wherein the identifying, by the mobile computing device and based on the image of the item, a classification of the item comprises:

transmitting the image of the item to an image recognition server; and

receiving, by the mobile computing device and from the image recognition server, a classification of the item.

14. The non-transitory computer-readable medium of claim 8, wherein the identifying, by the mobile computing device and based on the image of the item, a classification of the item comprises:

processing, by the mobile computing device, the image of the item with a neural network, the neural network trained to classify images of items.

15. A method, comprising:

receiving, from a mobile computing device, a video containing a plurality of frames depicting a plurality of items, each item tagged with a classification and a timestamp of when the item appears in the video;

retrieving, from a valuation database, an estimated valuation of each of the plurality of items;

tallying a total valuation of the plurality of items;

receiving additional information from the mobile computing device;

transmitting the total valuation of the plurality of items and the additional information to an insurance underwriting platform;

receiving, from the insurance underwriting platform, a plurality of insurance quotes for the plurality of items; and

transmitting the plurality of insurance quotes for the plurality of items to the mobile computing device.

16. The method of claim 15, wherein the additional information includes an indication of a location of the plurality of items.

17. The method of claim 16, further comprising:

receiving, from the mobile computing device, a location of the mobile computing device when the video was captured by the mobile computing device; and

comparing the location of the mobile computing device with the indication of a location of the plurality of items.

18. The method of claim 15, further comprising:

receiving an indication of an insurance claim from an insurance provider for at least one of the plurality of items; and

in response to receiving the indication of the insurance claim from the insurance provider for at least one of the plurality of items, transmitting the video containing frames depicting the plurality of items to the insurance provider.

19. The method of claim 15, further comprising:

transmitting the estimated valuation of each of the plurality of items to the mobile computing device;

receiving, the mobile computing device, adjustments to one or more of the estimated valuations; and

adjusting the total valuation of the plurality of items based on the adjustments to one or more of the estimated valuations.

20. The method of claim 15, further comprising:

receiving, from the mobile computing device, an indication of an insurance quote of the plurality of insurance quotes; and

associating the video containing frames depicting the plurality of items with the insurance quote.