US 12,406,476 B2
Image recognition edge device and method
Jun-Dong Chang, Taipei (TW)
Assigned to INSTITUTE FOR INFORMATION INDUSTRY, Taipei (TW)
Filed by INSTITUTE FOR INFORMATION INDUSTRY, Taipei (TW)
Filed on Nov. 28, 2022, as Appl. No. 18/058,878.
Claims priority of application No. 111144484 (TW), filed on Nov. 21, 2022.
Prior Publication US 2024/0169702 A1, May 23, 2024
Int. Cl. G06V 10/774 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/774 (2022.01) [G06V 10/82 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An image recognition edge device, comprising:
a memory, configured for storing a plurality of instructions; and
a processor, connected to the memory, and configured for executing an object recognition model, wherein the object recognition model comprises a plurality of convolutional layers and a combined fully connection layer, the plurality of convolutional layers are sequentially connected in sequence, and the combined fully connection layer comprises a first fully connection output layer and a second fully connection output layer, wherein the processor accesses the plurality of instructions to perform following operations:
downsampling an input image to generate a downsampled image;
inputting the downsampled image into the object recognition model thereby sequentially generating a plurality of feature tensors through the plurality of convolutional layers;
selecting a part of the plurality of feature tensors to form a first feature tensor pyramid;
selecting another part of the plurality of feature tensors to form a second feature tensor pyramid; and
inputting the first feature tensor pyramid and the second feature tensor pyramid into the combined fully connection layer, generating a first image detection label by the first fully connection output layer based on the first feature tensor pyramid, and generating a second image detection label by the second fully connection output layer based on the second feature tensor pyramid, wherein the first image detection label and the second image detection label respectively include an object identification result corresponding to the input image.