Image retrieval ranking method based on deep learning

Abstract

The invention discloses an image retrieval ranking method based on deep learning. The method includes the following steps: extracting low-level features of images in a query object and a training database, conducting high-level semantic learning and feature fusing through a deep network to obtain high-level features of multiple query object-image pairs and initially-determined parameters of the deep network, respectively conducting linear regression on the high-level features of the query object-image pairs to obtain ranking grades of the query object-image pairs, obtaining a ranking list of images in a training data set related to the query object, comparing the ranking list with a real ranking list of the images in the training data set to obtain pairing loss values of the image pairs related to the query object, adjusting the initially-determined parameters of the deep network to obtain the final parameters of the deep network, calculating the low-level features of a new query object, obtaining a deep network corresponding to the new query object, and conducting searching in the training data set to obtain an image list related to the deep network.

Description

technical field [0001] The invention relates to the technical field of image retrieval, in particular to an image retrieval and sorting method based on deep learning. Background technique [0002] In recent years, with the wide popularization of digital imaging equipment, the number of images on the Internet has grown explosively. How to accurately retrieve the image information that users want from the massive Internet images has broad application prospects and has become an important issue in the field of network multimedia. important research content. [0003] At present, the methods of large-scale search engines for Internet image retrieval mainly focus on the keyword-based search method. The user gives the text related to the desired picture, and the system searches for the picture corresponding to the text containing the query word according to the previously established matching of the text to the picture. Keyword-based retrieval methods have achieved certain result...

AI Technical Summary

Problems solved by technology

However, due to the diversity of information organization and the difficulty in determining the specific organization method, it is difficult to determine which information is related to the picture in the automatic extraction method, so it is difficult to extract accurate text information for the picture

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