Multiverse Computing, quantum computing solutions supplier, and IKERLAN, technology transfer centre, have partnered over detected defects in manufactured car pieces via image classification by quantum artificial vision systems.
The research team developed a quantum-enhanced kernel method for classification on universal gate-based quantum computers as well as a quantum classification algorithm on a quantum annealer. Researchers found that both algorithms outperformed common classical methods in the identification of relevant images and the accurate classification of manufacturing defects.
“This research is the first implementation of quantum computer vision for a relevant problem in a manufacturing production line,” said Ion Etxeberria, CEO of IKERLAN. “This collaborative study confirmed the benefits of applying quantum methods to real-world industrial challenges. We strongly believe that quantum computing will play a key role in providing AI-based solutions to particularly complex scenarios.”
“Quantum machine learning will significantly disrupt the automotive and manufacturing industries,” said Roman Orus, Ph.D., Chief Scientific Officer at Multiverse Computing. “We are pleased to witness the value of early applications in quantum computing today, such as quantum artificial vision, and excited to enter a new era of machine learning alongside forward-thinking partners like IKERLAN as quantum technology continues to advance.”
