US 11,893,083 B2
Electronic device and method for training or applying neural network model
Yi-Fan Liou, Hsin-Chu (TW); and Yen-Chun Huang, Hsin-Chu (TW)
Assigned to Coretronic Corporation, Hsin-Chu (TW)
Filed by Coretronic Corporation, Hsin-Chu (TW)
Filed on Sep. 7, 2021, as Appl. No. 17/467,453.
Claims priority of application No. 109132818 (TW), filed on Sep. 23, 2020.
Prior Publication US 2022/0092350 A1, Mar. 24, 2022
Int. Cl. G06F 18/214 (2023.01); G06N 3/04 (2023.01)
CPC G06F 18/214 (2023.01) [G06N 3/04 (2013.01)] 14 Claims
OG exemplary drawing
 
1. An electronic device for training or applying a neural network model, comprising:
a transceiver;
a storage medium configured to store multiple modules and the neural network model; and
a processor configured to couple to the storage medium and the transceiver, and configure to access and execute the modules, wherein the modules comprise:
a data collection module configured to receive an input data via the transceiver; and
a calculation module configured to perform convolution on the input data to generate a high-frequency feature map and a low-frequency feature map, and perform one of upsampling and downsampling to match a first size of the high-frequency feature map and a second size of the low-frequency feature map, concatenate the high-frequency feature map and the low-frequency feature map to generate a concatenated data, and input the concatenated data to an output layer of the neural network model.