Abstract: An image recognition method and an electronic apparatus configured for image recognition are provided. A training sample set is provided to train a recognition model including neural networks to recognize a classification label to which an image to be tested belongs through the trained recognition model. The training sample set includes image sets respectively belonging to users. During the training process, training images corresponding to classification labels are obtained from a first image set in the training sample set as reference images for training; a training image is obtained from a second image set different from the first image set as an input image for training; the reference images for training and the input image for training are obtained as inputs to the neural networks for training. The input to each neural network includes at least one of the reference images for training and the input image for training.