(Peer-Reviewed) Data-driven polarimetric approaches fuel computational imaging expansion
Sylvain Gigan
Laboratoire Kastler Brossel, École Normale Supérieure/PSL Research University, Paris 75005, France
Opto-Electronic Advances, 2024-09-28
Abstract
Incorporating polarization in computer vision tasks provides new solutions to high-level analytics, in particular when coupled with machine learning frameworks such as convolutional neural networks (CNN). A recent review in Opto-Electronic Science reports on the developments in data-driven polarimetric imaging, including polarimetric descattering, 3D imaging, reflection removal, target detection and biomedical imaging. The review carefully analyzes these new trends with their advantages and disadvantages, and provides a general insight for future research and development.
Triplet exciton harvesting via TADF in hafnium chlorides array scintillator screen enables ultrahigh-resolution X-ray imaging
Jun'an Lai, Yi Ye, Xu Liu, Sijun Cao, Shiji Zhou, Wenxia Zhang, Kang An, Peng He, Tingming Jiang, Xiaosheng Tang, Rui Zhou, Dong Zhang
Opto-Electronic Advances
2026-06-08
Vacancy oscillating mode in amorphous binary oxide film by terahertz time domain spectroscopy
Huan Liu, Haiyun Huang, Heng Yu, Zhi Gong, Fei Yu, Zheng Zhang, Zhiyong Tan, Juncheng Cao, Haiyun Liu, Kan-Hao Xue, Xiangshui Miao, Yan Liu, Yue Hao, Genquan Han, Qihua Xiong
Opto-Electronic Advances
2026-06-08