You can easily search for similar shapes from the library, significantly improving design efficiency.
This is an instructional video for searching chair shapes using Aries 3D-Matching products. It utilizes 3D shape recognition AI to search for similar chair shapes from the product library.
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basic information
Aries 3D-Matching utilizes 3D AI technology to directly recognize three-dimensional shapes created by 3D CAD or 3D scanners, enabling classification and search of shapes. The technology used in the product is a new method that directly recognizes three-dimensional shapes without relying on two-dimensional images, and it has been patented as an AI-based 3D shape search technology (Patent No. 7190147). The AI module is provided as a Windows executable module and can also be called and used from your current PLM system.
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There is a track record of use in automotive and machinery manufacturers.
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Company information
In the manufacturing industry, the use of three-dimensional data such as 3D CAD data is becoming widespread, but in AI, the use of two-dimensional data is mainstream, and the use of three-dimensional data is still not in sight. Our company is considering how to make better use of 3D CAD data in the manufacturing industry and contribute to improving QCD, and we are conducting research and development on three-dimensional shape recognition technology using AI and deep learning. Based on the latest AI research results, our company has successfully developed a three-dimensional AI model that can recognize three-dimensional shape data. With this groundbreaking three-dimensional AI technology, we will spread three-dimensional AI throughout the engineering chain centered on CAD, CAM, and CAE, contributing to the improvement of QCD. Moreover, three-dimensional AI is a new technology, and its potential is limitless. We will promote research and development of three-dimensional AI and spread this pioneering three-dimensional AI technology not only in the manufacturing industry but also in many other industries, contributing to the improvement of QCD.
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