Hyperspectral imaging is being extensively investigated owing to its promising future in critical applications such as medical diagnostics, sensing, and surveillance. However, current techniques are complex with multiple alignment-sensitive component...
A Mueller matrix (MM) provides a comprehensive representation of the polarization properties of a complex medium and encodes very rich information on the macro- and microstructural features. Histopathological features can be characterized by polariza...
The recent advent of diffractive deep neural networks or DNNs has opened new avenues for the design and optimization of multi-functional optical materials; despite the effectiveness of the DNN approach, there is a need for making these networks as we...
An improved deep neural network incorporating attention mechanism and DSSIM loss function (AM_U_Net) is used to recover input images with speckles transmitted through a multimode fiber (MMF). The network is trained on a relatively small dataset and d...
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morpholog...
Deep-brain microscopy is strongly limited by the size of the imaging probe, both in terms of achievable resolution and potential trauma due to surgery. Here, we show that a segment of an ultra-thin multi-mode fiber (cannula) can replace the bulky mic...
Light scattering is a pervasive problem in many areas. Recently, deep learning was implemented in speckle reconstruction. To better investigate the key feature extraction and generalization abilities of the networks for sparse pattern reconstruction,...
An integrated physical diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) substrate. This DONN has compact structure and can realize the function of machine learning with whole-passive fully-optical m...
In this paper, we introduce a deep learning-based spatio-temporal continuous human gesture recognition algorithm under degraded conditions using three-dimensional (3D) integral imaging. The proposed system is shown as an efficient continuous human ge...
In this study, an automatic algorithm has been presented based on a convolutional neural network (CNN) employing U-net. An ellipsoid and an ellipse were applied for approximation of a three-dimensional sweat duct and en face sweat pore at the differe...