US 11,735,315 B2
Method, apparatus, and device for fusing features applied to small target detection, and storage medium
Binghong Wu, Beijing (CN); Yehui Yang, Beijing (CN); Yanwu Xu, Beijing (CN); and Lei Wang, Beijing (CN)
Assigned to Beijing Baidu Netcom Science and Technology Co., Ltd., Beijing (CN)
Filed by BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD., Beijing (CN)
Filed on Mar. 26, 2021, as Appl. No. 17/213,896.
Claims priority of application No. 202011021013.9 (CN), filed on Sep. 25, 2020.
Prior Publication US 2021/0224581 A1, Jul. 22, 2021
Int. Cl. G16H 30/40 (2018.01); G06F 18/25 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01)
CPC G16H 30/40 (2018.01) [G06F 18/251 (2023.01); G06F 18/253 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01)] 15 Claims
OG exemplary drawing
 
1. A method for fusing features applied to small target detection, the method comprising:
acquiring feature maps output by convolutional layers in a Backbone network;
performing a convolution on the feature maps to obtain input feature maps of feature layers, the feature layers representing resolutions of the input feature maps; and
fusing, based on densely connection feature pyramid network features, the input feature maps of each feature layer to obtain output feature maps of the feature layers, the fusing comprising:
sampling an input feature map of an ith feature layer and input feature maps of other feature layers having resolutions lower than a resolution corresponding to the ith feature layer, i being a positive integer;
scaling, after the sampling, the input feature maps of the other feature layers to a same size as the input feature map of the ith feature layer; and
superimposing the input feature maps of the other feature layers after scaling and the input feature map of the ith feature layer one by one, and using a superimposed final result as an output feature map of the ith feature layer.