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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...

Abstract Kinematic airborne platforms are becoming increasingly vital for Earth observation. They highlight the critical need for accurate tropospheric delay corrections across varying altitudes, especially as most exist...

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...

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...

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 ...

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 Marine habitat maps are essential tools for marine spatial planning, providing information for decision‐making in conservation and resource management. Accurate classification of benthic habitats supports thei...

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...

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 Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

Experience-related plasticity is an essential component of networks involved in early olfactory processing. However, the mechanisms and functions of plasticity in these neural networks are not well understood. We studied...

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...