US 11,989,931 B2
Method and apparatus with object classification
Sangil Jung, Yongin-si (KR); Seungin Park, Yongin-si (KR); and Byung In Yoo, Seoul (KR)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed by SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed on Mar. 17, 2022, as Appl. No. 17/697,160.
Claims priority of application No. 10-2021-0126062 (KR), filed on Sep. 24, 2021.
Prior Publication US 2023/0095716 A1, Mar. 30, 2023
Int. Cl. G06V 10/80 (2022.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/806 (2022.01) [G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01)] 17 Claims
OG exemplary drawing
 
1. A processor-implemented object classification method, comprising:
receiving an input image;
storing first feature data extracted by a first feature extraction layer of a neural network configured to extract features of the input image;
receiving second feature data from a second feature extraction layer which is an upper layer of the first feature extraction layer;
generating merged feature data by merging the first feature data and the second feature data; and
classifying an object in the input image based on the merged feature data,
wherein the first feature data comprises a local feature of the input image, and the second feature data comprises a global feature of the input image, and
wherein the generating of the merged feature data comprises:
determining a weight to be applied to the first feature data;
applying the determined weight to the first feature data and determining first feature data to which the weight is applied; and
generating the merged feature data in which the global feature and the local feature are merged by merging the second feature data and the first feature data to which the weight is applied.