Cognex Acquires Vision Software Specialist SUALAB

Cognex Corp. has acquired vision software specialist SUALAB, strengthening the company’s position within the machine learning space. The addition of SUALAB’s engineering team and intellectual property is expected to enhance Cognex’s existing deep learning capabilities based on technology acquired from ViDi Systems in April 2017.

“Deep learning enables Cognex to solve many challenging inspection applications in factories, which, until now, could only be done by large teams of human visual inspectors,” said Robert J. Willett, president and CEO of Cognex. “SUALAB’s considerable IP, engineering expertise, and extensive market coverage will help us to serve a fast-growing market, primarily in Asia. Today, tens of thousands of people perform difficult, tedious, and error-prone visual inspections for flaws and defects on electronic components and subsystems, which will be done more reliably and at lower cost in the future with deep learning-based machine vision.”

Headquartered in Seoul, South Korea, SUALAB was co-founded in 2013 by Song Kiyoung, who will join Cognex and help lead the company’s engineers specializing in the use of deep learning for industrial machine vision applications. Cognex’s products include machine vision systems, machine vision sensors, and barcode readers, which use artificial intelligence.

Published: October 2019

Glossary

machine vision: Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
deep learning: Deep learning is a subset of machine learning that involves the use of artificial neural networks to model and solve complex problems. The term "deep" in deep learning refers to the use of deep neural networks, which are neural networks with multiple layers (deep architectures). These networks, often called deep neural networks or deep neural architectures, have the ability to automatically learn hierarchical representations of data. Key concepts and components of deep learning include: ...
artificial intelligence: The ability of a machine to perform certain complex functions normally associated with human intelligence, such as judgment, pattern recognition, understanding, learning, planning, and problem solving.

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