CPC G06F 18/214 (2023.01) [G06N 3/04 (2013.01)] | 14 Claims |
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.
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