US 12,443,828 B2
Method of lightweighting a neural network for object recognition, a method of recognizing object using the lightweighted neural network, and an electronic device for performing the same
Hyungjun Lee, Daejeon (KR); and Hancheol Park, Daejeon (KR)
Assigned to NOTA, INC., Daejeon (KR)
Filed by NOTA, INC., Daejeon (KR)
Filed on Oct. 30, 2024, as Appl. No. 18/932,549.
Claims priority of application No. 10-2023-0154173 (KR), filed on Nov. 9, 2023.
Prior Publication US 2025/0156696 A1, May 15, 2025
Int. Cl. G06N 3/0495 (2023.01); G06N 3/082 (2023.01); G06T 7/62 (2017.01); G06V 10/764 (2022.01)
CPC G06N 3/0495 (2023.01) [G06N 3/082 (2013.01); G06T 7/62 (2017.01); G06V 10/764 (2022.01)] 17 Claims
OG exemplary drawing
 
1. A method of compressing, by an electronic device, a neural network model for object recognition, the method comprising:
receiving an original model for object recognition trained based on a first data set;
receiving a second data set of an analysis target;
calculating object size information on sizes of objects included in an image of the second data set;
calculating performance decline rates for each object size of the original model according to pruning, based on the calculated object size information;
determining weight information on pruning ratios for each object size in consideration of the performance decline rates for each object size;
determining an optimized pruning ratio for the second data set of at least one layer included in the original model based on the determined weight information; and
generating a compressed neural network model from the original model by performing the pruning on the at least one layer based on the determined optimized pruning ratio, and
wherein the object size information includes information on a first ratio of first objects corresponding to a first size range included in the image and a second ratio of second objects corresponding to a second size range included in the image,
the first ratio is calculated based on number of the first objects in the image and total number of the total objects in the image including the first objects and the second objects, and
the second ratio is calculated based on number of the second objects in the image and the total number.