In recent years, 3D point clouds (PCs) have gained significant attention due to their diverse
applications across various fields, such as computer vision (CV), condition monitoring (CM) …

With the rapid development of new energy vehicles and electrochemical energy storage, the
demand for lithium-ion batteries has witnessed a significant surge. The expansion of the …

A bottleneck in high-throughput nanomaterials discovery is the pace at which new materials
can be structurally characterized. Although current machine learning (ML) methods show …

Point cloud is widely available in the manufacturing system with the continuous
development of 3-D sensors. Accurate point cloud segmentation can automatically identify …

The scarcity of defect samples and the imbalance of defect types lead to the fact that
achieving defect detection in color-patterned fabrics remains a challenge in the textile …

Detecting defects of yarn‐dyed fabrics automatically in industrial scenarios can improve
economic efficiency, but the scarcity of defect samples makes the task more challenging in …

This paper presents the first comprehensive literature review of deep learning (DL)
applications in additive manufacturing (AM). It addresses the need for a thorough analysis in …

Metamaterials are designed with intricate geometries to deliver unique properties, and
recent years have witnessed an upsurge in leveraging additive manufacturing (AM) to …

The emergence of modern robotic technology and artificial intelligence (AI) enables a
transformation in the textile sector. Manual fabric defect inspection is time-consuming, error …

With the advancement of 3D sensing technologies, point clouds are gradually becoming the
main type of data representation in applications such as autonomous driving, robotics, and …