Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …

Panchromatic and multispectral image fusion, termed pan-sharpening, is to merge the
spatial and spectral information of the source images into a fused one, which has a higher …

Membership regularized fuzzy clustering methods apply an important prior that neighboring
data points should possess similar memberships according to an affinity/similarity matrix. As …

This review explores the applications, challenges, and prospects of deep learning in the
microstructure analysis of alloy materials. First, it introduces the significance of alloy …

Semantic segmentation is one of the most challenging tasks in computer vision. However, in
many applications, a frequent obstacle is the lack of labeled images, due to the high cost of …

Metallographic images or often called the microstructures contain important information
about metals, such as strength, toughness, ductility, corrosion resistance, which are used to …

Understanding the fundamental microconstituents of metallic microstructure is crucial for
comprehending the physical and mechanical properties of the metal. Artificial Intelligence …

Understanding the stability of irradiation-induced voids in materials is important for
engineering material's swelling behavior under irradiation. In-situ TEM offers a spatial and …

Insufficient annotated samples coupled with class imbalance problem largely restrict the
wide application of deep learning (DL)-based approach in microstructure recognition and …

The quantification of the phase fraction is critical in materials science, bridging the gap
between material composition, processing techniques, microstructure, and resultant …