US 12,430,908 B2
Method and apparatus for diagnosing error of object placement using artificial neural network
Donghun Kim, Seoul (KR); Sang Soo Han, Seoul (KR); Leslie Tiong Ching Ow, Seoul (KR); Hyukjun Yoo, Seoul (KR); and Nayeon Kim, Seoul (KR)
Assigned to Korea Institute of Science and Technology, Seoul (KR)
Filed by KOREA INSTITUTE OF SCIENCE AND TECHNOLOGY, Seoul (KR)
Filed on Jun. 13, 2023, as Appl. No. 18/334,030.
Claims priority of application No. 10-2023-0059043 (KR), filed on May 8, 2023.
Prior Publication US 2024/0378881 A1, Nov. 14, 2024
Int. Cl. G06V 10/98 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/98 (2022.01) [G06V 10/82 (2022.01)] 12 Claims
OG exemplary drawing
 
1. An object placement error diagnosing method comprising:
inputting, to an artificial neural network, at least one input image representing a space in which at least one object is placed; and
acquiring data representing a diagnosis result of a placement error of the at least one object from an output of the artificial neural network,
wherein the artificial neural network comprises:
a main network configured to perform a convolution operation and a pooling operation on the at least one input image multiple times; and
a pyramid network configured to generate feature data of a plurality of stages for generating data representing the diagnosis result of the placement error of the at least one object by using a plurality of feature data generated in an operation process of the main network, and
feature data of an (N+1)-th stage among the feature data of the plurality of stages is generated by using any one feature data among the plurality of feature data generated in the operation process of the main network and feature data of an N-th stage among the feature data of the plurality of stages.