Multi-Scale Feature Attention Network for Polymer Classification using THz Dual-Comb Spectroscopy

This research proposes the Multi-Scale Feature Attention Network (MSFAN), a novel deep learning architecture for classifying 12 types of polymers using Terahertz Dual-Comb Spectroscopy (THz-DCS). This framework addresses the challenges of reliable polymer identification for recycled plastics by integrating feature gating and multi-scale parallel convolutions.