Material Classification

Material classification research aims to automatically identify and categorize materials based on their physical and chemical properties using various sensing modalities. Current efforts focus on developing robust algorithms, including deep learning architectures like convolutional neural networks and random forests, and integrating diverse data sources such as hyperspectral imaging, lidar, radar, and thermal imaging to improve classification accuracy and handle real-world complexities. This field is crucial for advancing robotics, autonomous systems, remote sensing, and manufacturing, enabling improved object recognition, scene understanding, and quality control.