BACKGROUND OF THE INVENTION

Field of the Disclosure

The present disclosure relates to information handling systems. More specifically, embodiments of the disclosure relate to a system and method using deep learning machine vision to categorize localities.

Description of the Related Art

As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. Options available to users include information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as customer record management, business projection analysis, etc. In addition, information handling systems may include a variety of hardware and software components that are configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.

SUMMARY

A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes the system to execute machine vision operations to categorize a locality. At least one embodiment includes a computer-implemented method including: accessing a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzing the map image to detect the entities in the locality using the geographical artefacts; assigning entity classes to detected entities in the locality; assigning a locality score to the locality based on entity classes included in the locality; retrieving street view images for one or more of the detected entities in the locality; and analyzing street view images of the detected entities to assign one or more further classifications to the detected entities. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

At least one embodiment includes a system having a processor; a data bus coupled to the processor; and a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and may include instructions executable by the processor and configured for: accessing a map image of a locality, where the map image includes geographical artifacts corresponding to entities within the locality; analyzing the map image to detect the entities in the locality using the geographical artefacts; assigning entity classes to detected entities in the locality; assigning a locality score to the locality based on entity classes included in the locality; retrieving street view images for one or more of the detected entities in the locality; and analyzing street view images of the detected entities to assign one or more further classifications to the detected entities.

At least one embodiment includes a non-transitory, computer-readable storage medium embodying computer program code, the computer program code may include computer-executable instructions configured for: accessing a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzing the map image to detect the entities in the locality using the geographical artefacts; assigning entity classes to detected entities in the locality; assigning a locality score to the locality based on entity classes included in the locality; retrieving street view images for one or more of the detected entities in the locality; and analyzing street view images of the detected entities to assign one or more further classifications to the detected entities.

