Automatically generate new shapes! The vehicle body can also be designed according to the designer's imagination.
"New Shape Synthesis" refers to the automatic generation of new shapes by blending feature vector quantities extracted from a properly trained AI model, similar to similarity judgment, across multiple shapes. A network using a type of deep learning called Variational Autoencoder (VAE) is constructed to create new vehicle body data. Multiple timings are established to add feature representations to the Decoder part of the VAE system, enhancing the generation results. 【Features】 ■ Automatically generates new shapes by blending feature vector quantities extracted from a properly trained AI model across multiple shapes. ■ Constructs a network using the VAE system to create new vehicle body data. ■ The time required for shape synthesis is just a few seconds, allowing designers to explore designs as they come to mind. *For more details, please refer to the PDF document or feel free to contact us.
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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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