6 papers
Metasurface-based Terahertz Three-dimensional Holography Enabled by Physics-Informed Neural Network
Jingzhu Shao, Ping Tang, Borui Xu +4
Artificial intelligence has revolutionized optical device design, overcoming the efficiency bottlenecks of traditional methods. For holographic metasurfaces, conventional iterative…
Fourier Transform Infrared microspectroscopy-based super-resolution virtual staining of unlabeled tissues by pixel Diffusion Transformer
Yudong Tian, Xiangyu Zhao, Yuqing Liu +2
Here, we present a diffusion transformer (DiT)-based pixel super-resolution virtual staining approach to transform low-resolution FTIR microspectroscopic images of the unstained ti…
Partitionable Diffractive Neural Networks for Multifunctional Optical Operations
Yudong Tian, Haifeng Xu, Yuqing Liu +3
Diffractive neural network (DNN), which can perform machine learning tasks based on the light propagation and diffraction, has recently emerged as a promising optical computing par…
Deep-learning-enabled inverse design of large-scale metasurfaces with full-wave accuracy
Borui Xu, Jingzhu Shao, Xiangyu Zhao +8
Recent advances in meta-optics have enabled diverse functionalities in compact optical devices; however, conventional forward design approaches become inadequate as device complexi…
Unsupervised and Supervised Algorithms for Identification of Sample Pixels in FTIR Images
Xiangyu Zhao, Yudong Tian, Jingzhu Shao +1
Mid-InfraRed spectroscopy is a promising label-free technique that can offer insights into morphological and pathological alterations in biological tissues at the molecular level.…
Metasurface-empowered freely-arrangeable multi-task diffractive neural networks with weighted training
Yudong Tian, Haifeng Xu, Yuqing Liu +4
Recent advancements in optical computing have garnered considerable research interests owing to its ener-gy-efficient operation and ultralow latency characteristics. As an emerging…