AI Medical Compendium Journal:
Applied optics

Showing 1 to 10 of 60 articles

Single-shot multispectral quantitative phase imaging of biological samples using deep learning.

Applied optics
Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly...

Optical computing powers graph neural networks.

Applied optics
Graph-based neural networks have promising perspectives but are limited by electronic bottlenecks. Our work explores the advantages of optical neural networks in the graph domain. We propose an optical graph neural network (OGNN) based on inverse-des...

Two-stage neural network via sensitivity learning for 2D photonic crystal bandgap maximization.

Applied optics
We propose a two-stage neural network method to maximize the bandgap of 2D photonic crystals. The proposed model consists of a fully connected deep feed-forward neural network (FNN) and U-Net, which are employed, respectively, to generate the shape f...

Noise-robust deep learning ghost imaging using a non-overlapping pattern for defect position mapping.

Applied optics
Defect detection requires highly sensitive and robust inspection methods. This study shows that non-overlapping illumination patterns can improve the noise robustness of deep learning ghost imaging (DLGI) without modifying the convolutional neural ne...

Instantaneous photosynthetically available radiation models for ocean waters using neural networks.

Applied optics
Instantaneous photosynthetically available radiation (IPAR) at the ocean surface and its vertical profile below the surface play a critical role in models to calculate net primary productivity of marine phytoplankton. In this work, we report two IPAR...

Resonance prediction and inverse design of multi-core selective couplers based on neural networks.

Applied optics
Resonance analysis and structural optimization of multi-channel selective fiber couplers currently rely on numerical simulation and manual trial and error, which is very repetitive and time consuming. To realize fast and accurate resonance analysis a...

Polarized light compass decoding.

Applied optics
The brains of some insects can encode and decode polarization information and obtain heading angle information. Referring to the encoding ability of insects, exponential function encoding is designed to improve the stability of the polarized light co...

Speckle classification of a multimode fiber based on Inception V3.

Applied optics
Multimode optical fiber plays an important role in endoscope miniaturization. With the development of deep learning and machine learning, neural networks can be used to identify and classify speckle patterns obtained at the fiber output. Based on the...

ICESat-2 laser data denoising algorithm based on a back propagation neural network.

Applied optics
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) photon data is the emerging satellite-based LiDAR data, widely used in surveying and mapping due to its small photometric spot and high density. Since ICESat-2 data collect weak signals, it is...

Polarization-driven camouflaged object segmentation via gated fusion.

Applied optics
Recently, polarization-based models for camouflaged object segmentation have attracted research attention. However, to construct this camouflaged object segmentation model, the main challenge is to effectively fuse polarization and light intensity fe...