Hyperspectral Imaging

Hyperspectral imaging (HSI) captures detailed spectral and spatial information across a wide range of wavelengths, enabling precise material identification and classification beyond the capabilities of traditional RGB imaging. Current research emphasizes improving HSI data processing through advanced deep learning architectures, including convolutional neural networks (CNNs), transformers, and graph neural networks (GNNs), often coupled with techniques like dimensionality reduction and knowledge distillation to address computational challenges and data limitations. These advancements are driving significant impact across diverse fields, from precision agriculture and medical diagnostics (e.g., brain tumor detection, sepsis prediction) to remote sensing and industrial applications like waste sorting, demonstrating HSI's potential for non-invasive, high-throughput analysis.