Rubber Material Retrieval System using Electron Microscope Images for Rubber Material Development

For developing valuable rubber materials, machine learning-based computer-aided analysis systems have been attracting a lot of attention. However, these systems mainly focus on analyzing the table and textual data, and the electron microscope images including the rich material information have not been enough analyzed. By effectively using these electron microscope images, further support for the material discovery is realized. In this paper, we present a material information retrieval system via electron microscope image space. Our system aims to support visually and comprehensively grasping the relationships between various rubber materials and those properties. By effectively using the electron microscope image space for material information retrieval, it is expected that the advances in material development are further accelerated.