Wavefront shaping (WFS) has been put forward several years ago to break the limitation caused by optical scattering in inhomogeneous medium, and realize optical focusing in disordered medium like biological tissues. However, usually, with traditional methods, WFS is time consuming and not cost efficient since it requires long time to obtain the information of the scattering medium. Here we propose the deep learning assisted wavefront shaping, which uses deep neural networks to predict the desired input optical modes that are needed to realize focusing after light passes through a scattering medium. Simulation results show that the pre-trained neural network is able to map output optical modes to input modes. Compared with previous methods w...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
Light scattering inside disordered media poses a significant challenge to achieve deep depth and hig...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Light scattering and aberrations limit optical microscopy in biological tissue, which motivates the ...
Imaging and delivering of light in a controlled manner through complex media such as glass diffusers...
Neural networks offer novel approaches for light control in microscopy. We compare different deep ne...
High-contrast imaging instruments are today primarily limited by non-common path aberrations appeari...
Deep neural networks (DNNs) are used to reconstruct transmission speckle intensity patterns from the...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
Light scattering inside disordered media poses a significant challenge to achieve deep depth and hig...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Scattering often limits the controlled delivery of light in applications such as biomedical imaging,...
Light scattering and aberrations limit optical microscopy in biological tissue, which motivates the ...
Imaging and delivering of light in a controlled manner through complex media such as glass diffusers...
Neural networks offer novel approaches for light control in microscopy. We compare different deep ne...
High-contrast imaging instruments are today primarily limited by non-common path aberrations appeari...
Deep neural networks (DNNs) are used to reconstruct transmission speckle intensity patterns from the...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...
We demonstrate that the deep learning algorithm can considerably simplify the design and characteriz...