"Machine-learning Method on Vectorized Three-Dimensional Model and Learning System Thereof" describes a novel method for utilizing vectorized 3D models to generate synthetic data of real-world objects for AI training. It can be applied for various applications, including object identification and anomaly detection, where training data are difficult or economically infeasible to acquire, and the robotic agents need these capabilities to function and swiftly interact with the p

The future of Physical AI isn't just about better technology—it's about smarter SDG implementation. Organizations that understand how to match SDG strategies with their specific Physical AI needs will gain significant competitive advantages.

How Corvus's synthetic data generation platform addresses the critical challenge of matching model capabilities with data requirements...

Transforming Industrial Inspection with Corvus For industrial manufacturers, the promise of AI for quality control is undeniable....

Key Takeaways Synthetic data generation has evolved from a niche research topic to an essential technology for AI development. The...

Author:  Ting-Yuan Wang, Solution Architect at Vizuro Realities of AI Implementation Over the past eight years, Vizuro has witnessed the rapid development and widespread application of AI across various industries. According to our client statistics, AI applications are most prevalent in the healthcare sector, accounting for 34%, followed by 25% in the pharmaceutical and life sciences industries, and 23% in manufacturing. Despite the enthusiasm and expectations surrounding AI

How CorePal uses GenAI to potentially recycle 98% of the valuable parts from junkyards to foster a circular economy With today's...

We are thrilled to announce that Vizuro has joined NVIDIA Inception , a program that nurtures startups revolutionizing industries with...