Metal characterization using Deep Learning image analysis

Webinar in English.

Wednesday 9 June - 13:00

Objective of the webinar

The rapid development of metals relies on understanding the microstructure of their materials (grain size, porosity, morphology, etc.), a reliable manufacturing process, and in-depth performance analysis for different applications. To solve some of the industry challenges (increasing throughput, providing defect-free products) and stay ahead of the competition, automated, reliable and intelligent analysis techniques are needed.

With Deep Learning and a powerful image analysis engine, MIPAR enables users to perform fast, accurate and automated image analysis. In three simple steps : plot, train and apply, researchers can create a template that identifies specific features, and then run custom parametric sheets on new images, to detect complex features in one to two seconds.

This webinar will present the benefits of using image segmentation analysis in metals using Deep Learning. This technique will allow you to analyze complex microstructures, perform automated grain and inclusion analysis. You will be able to study failures and defects, and analyze particles and satellites in additive manufacturing powders, with example applications in titanium, nickel, steel, and copper.

Event Registration

Free webinar, online.


Alisa Stratulat, PhD

Program Manager – MIPAR Image Analysis

Sammy Nordqvist
CEO – SciSpot Scientific Solutions