Cognex Releases In-Sight 2800 Vision System
Cognex Corporation has released the In-Sight 2800, the latest edition in its In-Sight series of vision systems for factory automation.
The newest offering is a full-featured vision system that combines deep learning technology with traditional rule-based vision tools to solve a range of applications from presence/absence detection to advanced categorization and sorting tasks.
“It has never been easier to apply deep learning to a production line”, said Carl Gerst, Executive Vice President of Products, Platforms and Solutions. “The In-Sight 2800 system can be trained with just a few images to automate everything from simple pass/fail inspections to advanced classification and sorting – no PC or programming is needed”.
The EasyBuilder interface guides users through the application development process step-by-step with a point-and-click setup. From here, the ViDi EL Classify can be trained to identify and sort defects into different categories and correctly identify parts with variation from a minimum of five images. The ability to classify by multiple features or characteristics allows users to solve more tasks with a single vision solution.
The vision system is capable of capturing high-resolution images of any product in any environment thanks to multi-colour lighting (RGBW) image formation, which maximises contrast and illumination, regardless of operating conditions. The new In-Sight 2800 system also offers a variety of accessories and field-changeable components to help users adapt to changes such as new parts, faster line speeds and higher quality standards.
The combination of deep learning and traditional vision tools is designed as such to solve a range of inspection applications where operators select the tool designed to deliver the highest possible accuracy for their task. Tools can be used individually for simple jobs or chained together for more complex logic sequences.
You can find more information about Cognex and the In-Sight 2800 vision system on its website.
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