Generation method, application method, training apparatus and application apparatus for neural network model, storage medium

A method of training a neural network model, the method comprising:

• compressing feature maps generated in an encoding stage of a U-shaped neural network model, wherein the feature maps are connected to a decoding stage of the U-shaped neural network model via skip connections, wherein the U-shaped neural network model includes at least the encoding stage and the decoding stage for processing image data;
• and
• generating, in the decoding stage, enhanced feature maps from compressed feature maps;
• calculating a predicted output result based on the constructed neural network model and data obtained from a training data set;
• and
• calculating a loss based on a loss function and the predicted output result to update parameters of a current neural network.

A apparatus that generates a neural network model comprising:

• at least one memory storing a program;
• and
• at least one processor that, upon execution of the program, is configured to operate as:
• a compressing unit that compresses feature maps generated in an encoding stage of a U-shaped neural network model, wherein the feature maps are connected to a decoding stage of the U-shaped neural network model via skip connections, wherein the U-shaped neural network model includes at least the encoding stage and the decoding stage for processing image data;
• and
• an enhancing unit that generates, in the decoding stage, enhanced feature maps from compressed feature maps.