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Biological neural network functionality depends on the vast number of connections between nodes, which can be challenging to implement artificially. One radical solution is to replace physical wiring with broadcasting of...

Materias / palabras clave: artificial neural networks; nanophotonics; neural network assisted photonic design; photonic neural networks

ABSTRACT A formation inversion algorithm with real‐time performance and accuracy is crucial for natural gamma logging while drilling (LWD). However, traditional inversion algorithms are often limited by high computatio...

A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of t...

Holograms which reconstruct the transverse profile of light with complex-amplitude information have demonstrated more excellent performances with an improved signal-to-noise ratio compared with those containing amplitude...

As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful a...

The optical properties of thin-film light emitting diodes (LEDs) are strongly dependent on their structures due to light interference inside the devices. However, the complexity of the design space grows exponentially wi...

Devices based on two-dimensional photonic-crystal nanocavities, which are defined by their air hole patterns, usually require a high quality (Q) factor to achieve high performance. We demonstrate that hole patterns with ...

ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and model integrity. We present a model‐inversion‐resistant physical unclon...

ABSTRACT Deep learning profoundly impacts various areas, such as face recognition and language translation. Owing to the increasingly high computational costs of training neural architectures, it is intractable to manual...

Major depressive disorder (MDD) with suicidal ideation or behaviour (MDSI) is associated with an increased risk of future suicide. The timely identification of suicide risk in patients with MDD and the subsequent impleme...

Post-traumatic stress disorder (PTSD) is a severe neuropsychiatric disorder characterised by re-experiencing, avoidance and hyperarousal. Memory abnormalities manifested as intrusive thoughts and prolonged distressful em...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

Abstract Multimodal neural interfaces that integrate electrical and optical functionalities are promising tools for neuroscientific and clinical applications that involve recording and manipulating neuronal activity. How...

Abstract This study investigated sex differences in neuromuscular responses during dynamic balance perturbations and isometric maximal voluntary contractions (IMVCs) by examining if menstrual cycle (MC) phase and the flu...

We demonstrate transfer learning as a tool to improve the efficacy of training deep learning models based on residual neural networks (ResNets). Specifically, we examine its use for study of multi-scale electrically larg...