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Deep Learning Streamlines Industrial Image Analysis for Material Inspections

Niamh Marriott, Editor

28/07/2021

Tags: News

LYMPUS Stream™ image analysis software now leverages the power of artificial intelligence to bring next-generation image segmentation to industrial microscope inspections.

Software version 2.5 adds Olympus’ TruAI™ deep-learning technology, enabling users to train neural networks to automatically segment and classify objects in microscope images for a range of material inspections. A trained network can be applied to future analyses for a similar application to maximize efficiency.

Accurate Image Segmentation
Image analysis is a critical part of many material science, industrial and quality assurance applications. However, image segmentation using conventional thresholding methods that depend on HSV or RGB color spaces can miss critical information or targets in samples. Olympus’ TruAI technology offers more accurate segmentation based on deep learning for a highly reproducible and robust analysis.

Easily Train and Manage Neural Networks
With the TruAI solution, users can easily train robust neural networks. An easy-to-use interface lets users efficiently label images and run trainings in batches. Networks can be configured with many input channels, trained to identify up to 16 classes, and imported or exported. The solution also offers options to review and edit training details.

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