The quick development of materials relies on the understanding of material microstructure (size, porosity, morphology, etc.), a reliable manufacturing process, and a thorough analysis of the performance for different applications. To solve some of the research challenges, automated, reliable, and intelligent analysis techniques are needed.
Using deep learning and a powerful image analysis engine, MIPAR (www.mipar.us) allows users to perform a fast, accurate and automated analysis of images. In three simple steps: trace, train and apply, researchers can create a model that identifies the features of interest and run personalized recipes on new images to detect complex features.
This presentation will overview the advantages of using modern analysis techniques to analyze particles, fibers and pores, droplets, defects, contaminants, and phases with real research applications.