US 11,721,088 B2
Image translation for image recognition to compensate for source image regional differences
Phillip Ellsworth Stahlfeld, Mountain View, CA (US)
Assigned to X Development LLC, Mountain View, CA (US)
Filed by X Development LLC, Mountain View, CA (US)
Filed on Aug. 26, 2021, as Appl. No. 17/458,095.
Application 17/458,095 is a continuation of application No. 16/666,304, filed on Oct. 28, 2019, granted, now 11,126,843.
Prior Publication US 2021/0383113 A1, Dec. 9, 2021
Int. Cl. G06F 17/15 (2006.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G06V 20/52 (2022.01); G06V 10/764 (2022.01); G06N 3/045 (2023.01)
CPC G06V 10/764 (2022.01) [G06F 17/15 (2013.01); G06N 3/045 (2023.01); G06V 10/82 (2022.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G06V 20/52 (2022.01)] 19 Claims
OG exemplary drawing
 
1. A method of predicting locations of utility assets, the method comprising:
receiving an input image of an area in a first geographical region, wherein the input image shows one or more utility assets in respective locations of the first geographical region;
generating, from the input image and using a generative adversarial network, a generative adversarial network output including a corresponding reference image, wherein the corresponding reference image shows the one or more utility assets in the same respective locations as the one or more utility assets shown in the input image; and
generating, by an object detection model and from the reference image, an object detection model output including bounding box data that identifies respective locations of one or more utility assets with reference to the input image.
 
9. A system comprising:
at least one processor; and a data store coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to perform operations comprising:
receiving an input image of an area in a first geographical region, wherein the input image shows one or more utility assets in respective locations of the first geographical region;
generating, from the input image and using a generative adversarial network, a generative adversarial network output including a corresponding reference image, wherein the corresponding reference image shows the one or more utility assets in the same respective locations as the one or more utility assets shown in the input image; and
generating, by an object detection model and from the reference image, an object detection model output including bounding box data that identifies respective locations of one or more utility assets with reference to the input image.
 
17. A non-transitory computer readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
receiving an input image of an area in a first geographical region, wherein the input image shows one or more utility assets in respective locations of the first geographical region;
generating, from the input image and using a generative adversarial network, a generative adversarial network output including a corresponding reference image, wherein the corresponding reference image shows the one or more utility assets in the same respective locations as the one or more utility assets shown in the input image; and
generating, by an object detection model and from the reference image, an object detection model output including bounding box data that identifies respective locations of one or more utility assets with reference to the input image.