Terracotta army fragment classification method based on deep learning

Abstract

The invention discloses a terracotta army fragment classification method based on deep learning, and the method comprises the steps: firstly carrying out the preprocessing of a terracotta army fragment data set, removing the background of a picture, cutting off the redundant white edges of the picture, unifying the specification images of the picture, and carrying out the normalization processing;then taking all the processed samples as a training set, randomly selecting part of the samples for labeling, importing the samples into the improved convolutional sparse auto-encoder network in batches for unsupervised iterative training until loss is small enough and tends to be stable, and obtaining output of a bottleneck layer as an effective feature; constructing an anchor graph according tothe effective features, and learning an anchor graph model by using an anchor graph semi-supervised classification algorithm based on a density peak value to obtain a prediction value of an unmarkedsample; and finally, selecting the category with the highest confidence as a prediction label, and comparing the prediction label with a real label to calculate classification accuracy. The method isconvenient to operate, and the problem that an existing method is not high in classification accuracy is solved.

Description

technical field [0001] The invention belongs to the field of cultural relics protection and the like, and relates to deep learning technology, in particular to a method for classifying fragments of Terracotta Warriors based on deep learning. Background technique [0002] In the field of cultural relic excavation and protection, the precise classification of cultural relic fragments is an important research content in this field. The terracotta warriors are the funeral objects of Qin Shihuang. They are huge in number, different in shape, and full of touching artistic charm. They are a golden business card of the splendid civilization of ancient my country. The Terracotta Warriors are rigid bodies of pottery, which are easily broken and broken if they are not well preserved. After natural wind erosion and historical changes, there are very few Qin Warriors pottery that can be completely preserved. The classification of the fragments of the Terracotta Warriors is an important ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method for classifying fragments of Terracotta Warriors based on deep learning to solve the problems of high dependence on experience, low measurement accuracy and inaccurate classification in the prior art

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