A Bayesian Based Deep Unrolling Algorithm for Single-Photon Lidar Systems-Reference-Cited by-同舟云学术

A Bayesian Based Deep Unrolling Algorithm for Single-Photon Lidar Systems

Author:

Koo Jakeoung¹^ORCID,Halimi Abderrahim¹^ORCID,McLaughlin Stephen¹^ORCID

Affiliation:

1. School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K.

Funder

Royal Academy of Engineering

Research Fellowship Scheme

Engineering and Physical Sciences Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

Reference52 articles.

1. Dropout as a bayesian approximation: Representing model uncertainty in deep learning;gal;Proc Int Conf Mach Learn,0

2. Attend and tell: Neural image caption generation with visual attention;xu;Proc Int Conf Mach Learn,0

3. Attention is all you need;vaswani;Proc Neural Inf Process Syst,0

4. Robust learned shrinkage-thresholding (REST): Robust unrolling for sparse recover;pu,2021

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