Image recognition method and apparatus, and device and medium

An electronic device, comprising a memory and one or more processors, wherein a computer-readable instruction is stored in the memory, and the computer-readable instruction, when executed by the one or more processors, causes the one or more processors to perform operations comprising:

• acquiring an image training sample data set;
• wherein the image training sample data set comprises image training sample data and tag information corresponding to the image training sample data;
• constructing a basic activation function and a preset bias adjustment function as a preset activation function in an addition relationship, and determining the preset activation function to be an activation function of a neural network model, to obtain an initial neural network model;
• wherein, the preset bias adjustment function is a function constructed from a symbol function, a first trainable parameter and a quadratic term in a multiplication relationship;
• inputting the image training sample data set into the initial neural network model for training until the model converges, to obtain a trained neural network model;
• and
• when an image to be recognized is acquired, outputting a recognition result corresponding to the image to be recognized by using the trained neural network mode.

One or more non-transitory computer-readable storage media storing a computer-readable instruction, wherein the computer-readable instruction, when executed by one or more processors, causes the one or more processors to perform operations comprising:

• acquiring an image training sample data set;
• wherein the image training sample data set comprises image training sample data and tag information corresponding to the image training sample data;
• constructing a basic activation function and a preset bias adjustment function as a preset activation function in an addition relationship, and determining the preset activation function to be an activation function of a neural network model, to obtain an initial neural network model;
• wherein, the preset bias adjustment function is a function constructed from a symbol function, a first trainable parameter and a quadratic term in a multiplication relationship;
• inputting the image training sample data set into the initial neural network model for training until the model converges, to obtain a trained neural network model;
• and
• when an image to be recognized is acquired, outputting a recognition result corresponding to the image to be recognized by using the trained neural network model.