eHoloNet: a learning-based end-to-end approach for in-line digital holographic reconstruction

Parallel lensless compressive imaging via deep convolutional neural networks

(2018) Xin Yuan et al.   OPTICS EXPRESS

Recent advances in convolutional neural networks

(2018) Jiuxiang Gu et al.   PATTERN RECOGNITION

Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow

(2018) Shaowei Jiang et al.   Biomedical Optics Express

Learning-based nonparametric autofocusing for digital holography

(2018) Zhenbo Ren et al.   Optica

Extended depth-of-field in holographic imaging using deep-learning-based autofocusing and phase recovery

(2018) Yichen Wu et al.   Optica

Convolutional Neural Networks for Inverse Problems in Imaging: A Review

(2017) Michael T. McCann et al.   IEEE SIGNAL PROCESSING MAGAZINE

Deep Convolutional Neural Network for Inverse Problems in Imaging

(2017) Kyong Hwan Jin et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection

(2017) Thanh Nguyen et al.   OPTICS EXPRESS

Phase recovery and holographic image reconstruction using deep learning in neural networks

(2017) Yair Rivenson et al.   Light-Science & Applications

Lensless computational imaging through deep learning

(2017) Ayan Sinha et al.   Optica

Deep-learning-based ghost imaging

(2017) Meng Lyu et al.   Scientific Reports

Learning-based imaging through scattering media

(2016) Ryoichi Horisaki et al.   OPTICS EXPRESS

Deep learning

(2015) Yann LeCun et al.   NATURE

Iterative solution to twin image problem in in-line digital holography

(2013) Lu Rong et al.   OPTICS AND LASERS IN ENGINEERING

Simultaneous reconstruction of phase and amplitude contrast from a single holographic record

(2009) Tatiana Latychevskaia et al.   OPTICS EXPRESS

Two-step-only quadrature phase-shifting digital holography

(2009) Jung-Ping Liu et al.   OPTICS LETTERS