US 11,989,948 B1
Accelerated non-maximum suppression in machine learning applications
Zhimeng Fan, Shanghai (CN)
Assigned to Nvidia Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Oct. 13, 2021, as Appl. No. 17/500,167.
Int. Cl. G06V 20/58 (2022.01); G06F 7/24 (2006.01); G06F 7/499 (2006.01); G06F 18/2431 (2023.01)
CPC G06V 20/58 (2022.01) [G06F 7/24 (2013.01); G06F 7/49915 (2013.01); G06F 18/2431 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A method of performing a non-maximum suppression (NMS) algorithm, the method comprising:
identifying a plurality of bounding boxes corresponding to one or more objects associated with one or more digital images, wherein each of the plurality of bounding boxes is associated with a confidence score in a first set of confidence scores;
transforming the first set of confidence scores into a second set of confidence scores within a specified interval, wherein a first portion of each confidence score in the second set of confidence scores is the same;
sorting the confidence scores in the second set of confidence scores in a descending order according to a remaining portion of each confidence score in the second set of confidence scores; and
performing a first suppression operation on the second set of confidence scores to remove one or more redundant bounding boxes from the plurality of bounding boxes.