Pleora and Neurocle Simplify AI Training and Deployment with Plug and Play Solution for Visual Inspection

AI Gateway “no code” Inspection plug-In significantly reduces development and deployment efforts for advanced classification, segmentation, and detection capabilities

Pleora Technologies and Neurocle announced a technology partnership that simplifies the deployment of deep learning-based classification, segmentation, and object detection capabilities for visual inspection applications. Lead customers are evaluating the AI Gateway and Inspection plug-in developed with Neurocle to reduce errors, false-positives, and secondary screenings in packaging, pharmaceutical, and finished goods analysis applications.

“Pleora’s AI Gateway and plug-in skills help organizations quickly realize the business benefits of machine learning, without costly, time-consuming algorithm development or replacing existing infrastructure,” said Jonathan Hou, Chief Technology Officer, Pleora Technologies. “Working with partners including Neurocle, we’re delivering a unique evolutionary approach to AI that enables quick deployment and continuous training to improve results and lower costs of visual inspection and quality control.”

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With the Pleora AI Gateway and Inspection plug-In, end-users and integrators can deploy machine learning visual inspection capabilities without any additional programming. Images and data are simply uploaded to Neurocle’s Neuro-T, deep learning vision software which supports a unique “Auto Deep Learning” technology with predefined parameters optimized for the NVIDIA GPU in Pleora’s AI Gateway. With Pleora’s “no code” approach, AI models are transferred and deployed on the AI Gateway for production environments. In comparison to this plug and play approach, traditional AI algorithm development requires multiple time-consuming steps and dedicated coding to input images, label defects, fine-tune training, and optimize models.

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The AI Gateway handles image acquisition from any vision standard-compliant image source and sends out the processed data over GigE Vision to inspection and analysis platforms. This means end-users can avoid vendor lock-in while maintaining infrastructure, processes, and analysis software.

In a quality inspection application, for example, the AI Gateway intercepts the camera image feed and applies the selected Inspection plug-in skills. The gateway then sends the AI processed data to the inspection application, which seamlessly receives the video as if it were still connected directly to the camera. Similarly, the AI Gateway can process imaging data with loaded plug-in skills in parallel to traditional processing tools. If a defect is detected, processed video from the AI Gateway can confirm or reject results as a secondary inspection.

“Neuro-T is a user-friendly approach that enables deep learning for visual inspection with just a few clicks,” said Hongsuk Lee, Chief Executive Officer, Neurocle. “Developing a plug-in solution for the Pleora AI Gateway, we’re making inspection systems plug and play, enabling automation for manual quality control checks and improving performance of existing systems with deep learning technology.”