Material Identification in Complex Environments: Neural Network Approaches to Hyperspectral Image Analysis
This study examines plastic identification in complex hyperspectral scenes, where illumination, background materials, spectral mixing, and within-class variation make pixel-level classification substantially harder than controlled laboratory sorting. The data include both visible and near-infrared measurements, making it possible to compare the practical value of different wavelength ranges.
Oct 1, 2023