- April 24, 2020
- Pleora Technologies
The technology partnership will work to simplify the deployment of deep learning-based classification, segmentation, and object detection capabilities for visual inspection applications.
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.
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.
Pleora’s AI Gateway provides additional plug-in AI skills for hyperspectral imaging, with the processing flexibility of an NVIDIA GPU to deploy open source or custom algorithms developed in popular frameworks like TensorFlow and OpenCV. Click Here for More Information
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