AI Medical Compendium Journal:
Optics letters

Showing 11 to 20 of 56 articles

Effects of interlayer reflection and interpixel interaction in diffractive optical neural networks.

Optics letters
Multilayer diffractive optical neural networks (DONNs) can perform machine learning (ML) tasks at the speed of light with low energy consumption. Decreasing the number of diffractive layers can reduce inevitable material and diffraction losses to imp...

Coded aperture compressive temporal imaging using complementary codes and untrained neural networks for high-quality reconstruction.

Optics letters
The coded aperture compressive temporal imaging (CACTI) modality is capable of capturing dynamic scenes with only a single-shot of a 2D detector. In this Letter, we present a specifically designed CACTI system to boost the reconstruction quality. Our...

Prediction of metasurface spectral response based on a deep neural network.

Optics letters
The two-dimensional optical metasurface can realize the free regulation of light waves through the free design of structure, which is highly appreciated by researchers. As there are high requirements for computer hardware, long time for simulation ca...

Spatially variant deblur and image enhancement in a single multimode fiber imaged by deep learning.

Optics letters
A single multimode fiber has been applied in minimally invasive endoscopy with wavefront shaping for biological research such as brain imaging. Most of the fibers, such as step-index and graded-index multimode fibers, give rise to spatially variant b...

Sparse phase retrieval using a physics-informed neural network for Fourier ptychographic microscopy.

Optics letters
In this paper, we report a sparse phase retrieval framework for Fourier ptychographic microscopy using the recently proposed principle of physics-informed neural networks. The phase retrieval problem is cast as training bidirectional mappings from th...

Tunable grating surfaces with high diffractive efficiency optimized by deep neural networks.

Optics letters
High diffractive efficiency gratings, as a core component in optics, can engineer light transport and separation. This Letter predicts a grating surface with high diffractive efficiency within the visible light wave band with the aid of deep neural n...

Dynamic intelligent measurement of multiple chirped signals of different types based on the optical computing STFT and the YOLOv3 neural network.

Optics letters
We propose a simultaneous measurement system for multiple signals of different types which combines the optical computing short-time Fourier transform (STFT) and You Only Look Once (YOLOv3) neural network. Through the system, the analytical expressio...

Non-invasive imaging through scattering medium and around corners beyond 3D memory effect.

Optics letters
The three-dimensional (3D) memory effect (ME) has been shown to exist in a variety of scattering scenes. Limited by the scope of ME, speckle correlation technology only can be applied in a small imaging field of view (FOV) with a small depth of field...

Lensless computational imaging with a hybrid framework of holographic propagation and deep learning.

Optics letters
Lensless imaging has attracted attention as it avoids the bulky optical lens. Lensless holographic imaging is a type of a lensless imaging technique. Recently, deep learning has also shown tremendous potential in lensless holographic imaging. A label...

Optical processor for a binarized neural network.

Optics letters
We propose and experimentally demonstrate an optical processor for a binarized neural network (NN). Implementation of a binarized NN involves multiply-accumulate operations, in which positive and negative weights should be implemented. In the propose...