KMTL and Yokohama National University have formed an integrated-research consortium for Fractography and Deep Learning (FraD).
Yokohama National University (Center for Creation of Symbiosis Society with Risk, Institute of Advanced Sciences), National Institute of Occupational Safety and Health, and KMTL jointly formed an industry-academia-government collaboration consortium, “Integrated-research Consortium for Fractography and Deep Learning (operated as FraD)”. The purpose is to establish AI-based innovative fracture-surface-image-analysis technology that aids in preventing various accidents caused by metal fractures.
The field of fracture surface analysis has problems such as shortage of skilled fracture-surface analysts and how to inherit the analysis techniques. On the other hand, AI, especially in deep learning, is maturing, and has achieved highly accurate classification especially for image recognition. Applying the deep-learning technology to fracture surface analysis will assist beginners in analysis and it can be a breakthrough in solving the existing problems. However, such system will not be developed by a single researcher or laboratory because of a large amount of data required.
KMTL is determined to solve these problems as the lead managing company of the consortium, working with public institutions including Yokohama National University and National Institute of Occupational Safety and Health.
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|Press Release of Yokohama National University (July 8)||News Release of IAS Center for Creation of Symbiosis Society with Risk, Yokohama National University (July 8)|
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