Bioinformatics (Oxford, England)
Dec 13, 2022
SUMMARY: In recent years, Deep Learning (DL) has been increasingly used in many fields, in particular in image recognition, due to its ability to solve problems where traditional machine learning algorithms fail. However, building an appropriate DL m...
Applied optics
Dec 10, 2022
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...
Optics express
Dec 5, 2022
Solving the inverse problem is a major challenge in contemporary nano-optics. However, frequently not just a possible solution needs to be found but rather the solution that accommodates constraints imposed by the problem at hand. To select the most ...
Optics express
Dec 5, 2022
Neural network-based inverse lithography technology (NNILT) has been used to improve the computational efficiency of large-scale mask optimization for advanced photolithography. NNILT is now mostly based on labels, and its performance is affected by ...
Physical review. E
Dec 1, 2022
In the studies of network structures, much attention has been devoted to developing approaches to reconstruct networks and predict missing links when edge-related information is given. However, such approaches are not applicable when we are only give...
Physical review. E
Dec 1, 2022
One of the main questions regarding complex systems at large scales concerns the effective interactions and driving forces that emerge from the detailed microscopic properties. Coarse-grained models aim to describe complex systems in terms of coarse-...
Applied optics
Dec 1, 2022
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...
Applied optics
Dec 1, 2022
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...
Chaos (Woodbury, N.Y.)
Dec 1, 2022
Biological neurons can exhibit complex coexisting multiple firing patterns dependent on initial conditions. To this end, this paper presents a novel adaptive synapse-based neuron (ASN) model with sine activation function. The ASN model has time-varyi...
Journal of the Optical Society of America. A, Optics, image science, and vision
Dec 1, 2022
Speckle reconstruction is a classical inverse problem in computational imaging. Inspired by the memory effect of the scattering medium, deep learning methods reveal excellent performance in extracting the correlation of speckle patterns. Nowadays, ad...