# Evaluating the Visual Similarity of Southwest China's Ethnic Minority Brocade Based on Deep Learning

arXiv: https://arxiv.org/abs/2408.14060 · HTML: https://mlsanity.com/paper/2408.14060/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2024.

## Abstract (arXiv)

This paper employs deep learning methods to investigate the visual similarity of ethnic minority patterns in Southwest China. A customized SResNet-18 network was developed, achieving an accuracy of 98.7% on the test set, outperforming ResNet-18, VGGNet-16, and AlexNet. The extracted feature vectors from SResNet-18 were evaluated using three metrics: cosine similarity, Euclidean distance, and Manhattan distance. The analysis results were visually represented on an ethnic thematic map, highlighting the connections between ethnic patterns and their regional distributions.