(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.
Multifunctional mixed analog/digital signal processor based on integrated photonics
Yichen Wu, Qipeng Yang, Bitao Shen, Yuansheng Tao, Xuguang Zhang, Zihan Tao, Luwen Xing, Zhangfeng Ge, Tiantian Li, Bowen Bai, Haowen Shu, Xingjun Wang
Opto-Electronic Science
2024-08-16