Learning-Based THz Multi-Layer Imaging for High-Capacity Positioning

This paper considers terahertz (THz) multi-layer imaging for three-dimensional (3D) positioning and encoders. A learning-based approach is introduced to address challenges such as 1) depth variation, 2) shadowing effect, and 3) content recognition at the back surface of each layer. Experimental validation on a three-layer sample with contents on both front and back surfaces confirms the effectiveness of the proposed approach.