Deep learning technology to be featured prominently at VISION 2018

July 6, 2018
Deep learning represents a growth segment in machine vision, and as a result, will be a technology that is prominently featured at VISION 2018 in Stuttgart from November 6-8.

Deep learning represents a growth segment in machine vision, and as a result, will be a technology that is prominently featured at VISION 2018 in Stuttgart from November 6-8.

For anyone who has attended a recent show, stays up to date with news, or is otherwise involved in machine vision, this is not going to come as a surprise. However, the team behind VISION lists deep learning technology as one of the reasons why this year’s event will be one of the best yet.

"On 6-8 November in Stuttgart, it’s going to be tremendously exciting to see how exhibitors present a topic as talked-about as deep learning and link it to conventional machine vision, as well as embedded vision," said Florian Niethammer, project manager for VISION at Messe Stuttgart "In line with our campaign motto, ‘BE VISIONARY’, we’re expecting a veritable explosion of new products and solutions that many wouldn’t have even imagined just two years ago at the last VISION."

Deep learning is an area of machine learning that enables computers to be trained and learn through architectures such as convolutional neural networks (CNNs). It imitates the way the human brain works by processing data and creating patterns for use in decision making. As of late, several machine vision software companies have deployed the technology within their products, while others base their entire product on it.>>> Learn more about these companies here.

"The strength of deep learning lies in how its approach can take more flexible decisions than the sets of predefined rules you find in conventional machine-vision systems," said Volker Gimple, who heads the machine vision group at Stemmer Imaging, in a VISION press release.

Dr. Klaus-Henning Noffz, managing director of Silicon Software, agreed: "Deep learning offers an edge whenever you have test objects with large variations that make them difficult to model mathematically."

He also provided an example, citing an automotive application where deep learning is being used to handle the classification of a test object in question: "With the help of deep learning, self-learning algorithms can detect every single tiny flaw in the paint – even those invisible to the naked eye."

One company that will showcase their deep learning technology at VISION for the first time is Deepsense, which offers a solution for visual quality control that is adept at inspecting objects with complex patterns—such as wood or textiles—without the need for tedious manual configuration. Robert Bogucki, chief science officer at Deepsense, also noted in the press release that he sees great potential in applying deep learning to the field of healthcare in the future.

Another hot topic in machine vision, as of late, is embedded vision. At VISION 2018, deep learning and embedded vision will intersect, as many companies are now deploying deep learning on embedded devices. Examples include the NVIDIA Jetson TX2 embedded board supporting the deep learning inference in MVTec’s HALCON software, as well as a forthcoming solution from Silicon Software that involves deep learning running on a VisualApplets environment on an FPGA. Additionally, Irida Labs will present its DeepAPI framework, which is a library for implementing deep learning on any embedded device.

Beyond these companies, there are sure to be others that will be showcasing their deep learning technologies and demonstrations as it becomes increasingly popular and prevalent in the marketplace. Keep an eye on announcements relating to deep learning and VISION 2018 as the world’s biggest machine vision tradeshow gets closer.

View the VISION press release.

Pictured: An embedded vision system for identifying and counting people and vehicles via region-based convolutional neural networks (Neadvance)

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About the Author

James Carroll

Former VSD Editor James Carroll joined the team 2013.  Carroll covered machine vision and imaging from numerous angles, including application stories, industry news, market updates, and new products. In addition to writing and editing articles, Carroll managed the Innovators Awards program and webcasts.

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