Self-adaptive neural network training method for image recognition

The invention discloses a self-adaptive neural network training method for image recognition. The method comprises the steps: acquiring and preprocessing an image data set; constructing a convolutional neural network model, and setting an adaptive loss function; inputting the preprocessed image data into a convolutional neural network model for forward propagation to obtain a feature vector and a classification layer weight of the image; calculating an adaptive loss function according to the image feature vector and the classification layer weight, and judging whether the convolutional neural network model converges; performing back propagation on the convolutional neural network model according to the adaptive loss function, and updating the weight of the classification layer; and progressively increasing the number of iterations, and updating the adaptive loss function. Compared with a softmax-based classification loss function training method, the method provided by the invention has the advantages that th