Neural network training method and apparatus for image retrieval, and electronic device

A neural network training apparatus for image retrieval, wherein a neural network comprises:

• one feature extractor and a plurality of learners, and the plurality of learners share features extracted by the one feature extractor;
• the apparatus predetermines a plurality of training image groups, and each training image group comprises three images, wherein two images are of the same category and one image is of a different category;
• for each training image group, a random weight is assigned to each learner;
• and the apparatus comprises:
• an extracting unit configured for, for each training image group, inputting the three images of the training image group into the feature extractor, and determining features of the three images;
• a weighting unit configured for, for each training image group and for each image, respectively multiplying the features of the image by the random weight corresponding to each learner, so as to obtain weighted features of the image corresponding to each learner;
• and for each learner, making the three images in the training image group correspond to the same random weight;
• a mapping unit configured for, for each training image group and for each image, inputting the weighted features of the image corresponding to each learner into the corresponding learner, and determining a plurality of feature vectors of the image;
• and
• an adjusting unit configured for adjusting parameters of the neural network based on the plurality of feature vectors of each image in each training image group of the plurality of training image groups;
• wherein a different random weight is reassigned to each learner every time when one training image group is changed to another training image group, while the random weight corresponding to each learner remains unchanged in processing the three images of the same training image group.