Artificial intelligence system for image similarity analysis using optimized image pair selection and multi-scale convolutional neural networks

摘要

At an artificial intelligence system, a neural network model is trained iteratively to generate similarity scores for image pairs. The model includes a first subnetwork with a first number of convolution layers, and a second subnetwork with a different number of convolution layers. A given training iteration includes determining, using a version of the model generated in an earlier iteration, similarity scores for a set of image pairs, and then selecting a subset of the pairs based on the similarity scores. The selected subset is used to train a subsequent version of the model. After the model is trained, it may be used to generate similarity scores for other image pairs, and responsive operations may be initiated if the scores meet a criterion.