Study on Artifact Classification Identification Based on Deep Learning

Abstract

Deep learning is a hot technology developed in the field of artificial intelligence in recent years. It extracts complex content, simulates the hierarchical structure of the human brain, and constantly adjusts the parameters to find the optimal prediction results. This paper introduces the implementation principle and process of deep learning, uses the deep learning method to study the artifact classification and identification, and completes the artifact classification and identification experiment through the training model of various artifacts. The experimental results show that the sufficient training of the samples can have a high identification accuracy, but the identification accuracy needs to be further strengthened in practical application environments.