most citedHybrid Multi-Head Physics-informed Neural Network for Depth Estimation in Terahertz Imaging

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

physics.optics2024

Reconstruction of partially occluded objects with a physics-driven self-training neural network

Mingjun Xiang, Kai Zhou, Hui Yuan +1

This study proposes a novel approach utilizing a physics-informed deep learning (DL) algorithm to reconstruct occluded objects in a terahertz (THz) holographic system. Taking the a…

physics.optics2024★ 1 cited

Hybrid Multi-Head Physics-informed Neural Network for Depth Estimation in Terahertz Imaging

Mingjun Xiang, Hui Yuan, Kai Zhou +1

Terahertz (THz) imaging is one of the hotspots in the field of optics, where the depth information retrieval is a key factor to restore the three-dimensional appearance of objects.…

physics.optics2022

Amplitude/Phase Retrieval for Terahertz Holography with Supervised and Unsupervised Physics-Informed Deep Learning

Mingjun Xiang, Hui Yuan, Lingxiao Wang +2

Recently, digital holographic imaging techniques (including methods with heterodyne detection) have found increased attention in the terahertz (THz) frequency range. However, holog…