| CPC G06F 18/2431 (2023.01) [G06F 16/55 (2019.01); G06T 7/001 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/20036 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30108 (2013.01)] | 20 Claims |

|
1. A computer-implemented method comprising:
accessing a first database holding information encoding a set of labels, wherein the set of labels specify a condition of at least one of: a surface pipe, or an underground enclosure, wherein the underground enclosure includes a casing or a tubing, either of which runs at a plurality of depth locations;
accessing a second database holding a plurality of inspection logs, wherein the plurality of inspection logs record measurement data of the at least one of the surface pipe or the underground enclosure that runs at the plurality of depth locations;
based on, at least in part, the set of labels and the plurality of inspection logs, training a deep learning model configured to classify, into the set of labels, the condition of the at least one of the surface pipe or the underground enclosure that runs at the plurality of depth locations, when presented with the inspection logs;
applying the deep learning model to one or more newly received inspection logs containing measurement data of a new surface pipe or a new underground enclosure; and
subsequently classifying, into the set of labels, the condition of the new surface pipe or the new underground enclosure.
|