A Collaborative Jade Recognition System for Mobile Devices Based on Lightweight and Large Models

TL;DR

This paper introduces a novel mobile jade recognition system that combines multi-scale image analysis and collaborative models to achieve high accuracy and efficiency in resource-constrained environments.

Contribution

It presents a size model based on multi-scale processing and a collaborative multi-model framework integrating deep learning and traditional methods for mobile jade recognition.

Findings

High recognition accuracy on mobile devices

Fast processing with low computational resources

Effective in diverse environments

Abstract

With the widespread adoption and development of mobile devices, vision-based recognition applications have become a hot topic in research. Jade, as an important cultural heritage and artistic item, has significant applications in fields such as jewelry identification and cultural relic preservation. However, existing jade recognition systems still face challenges in mobile implementation, such as limited computing resources, real-time requirements, and accuracy issues. To address these challenges, this paper proposes a jade recognition system based on size model collaboration, aiming to achieve efficient and accurate jade identification using mobile devices such as smartphones.First, we design a size model based on multi-scale image processing, extracting key visual information by analyzing jade's dimensions, shapes, and surface textures. Then, a collaborative multi-model classification framework is built by combining deep learning and traditional computer vision algorithms. This framework can effectively select and adjust models based on different jade characteristics, providing high accuracy results across various environments and devices.Experimental results show that the proposed system can provide high recognition accuracy and fast processing time on mobile devices, while consuming relatively low computational resources. The system not only holds great application potential but also provides new ideas and technical support for the intelligent development of jade identification.