| CPC G06V 20/176 (2022.01) [G01C 11/08 (2013.01); G06V 10/82 (2022.01)] | 14 Claims |

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1. A computer-implemented method comprising:
processing a plurality of images using a machine learning model to generate a plurality of redundant observations of a pole-like object respectively depicted in the plurality of images;
performing a photogrammetric triangulation of the plurality of redundant observations to determine three-dimensional coordinate data of the pole-like object, wherein the machine learning model generates the plurality of redundant observations based on detecting one or more semantic keypoints comprising a geometric representation of the pole-like object, and wherein the three-dimensional coordinate data include respective three-dimensional coordinates of the one or more semantic keypoints;
determining a location, a geometric attribute, or a combination thereof of the pole-like object based on the three-dimensional coordinate data; wherein the geometric attribute includes a length, an orientation, or a combination thereof; and
providing the three-dimensional coordinate data and the geometric attribute of the pole-like object as an output.
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