Recent advances in image data proccesing through deep learning allow for new
optimization and performance-enhancement schemes for radiation detectors and imaging …

Photonic integrated circuits are facilitating the development of optical neural networks, which
have the potential to be both faster and more energy efficient than their electronic …

Spiking neural networks (SNNs) utilize brain-like spatiotemporal spike encoding for
simulating brain functions. Photonic SNN offers an ultrahigh speed and power efficiency …

The wide adoption and significant computing resource cost of attention-based transformers,
eg, Vision Transformers and large language models, have driven the demand for efficient …

The collective dynamics in neural networks is essential for information processing and has
attracted much interest on the application in artificial intelligence. Synchronization is one of …

Analog computing has been recognized as a promising low-power alternative to digital
counterparts for neural network acceleration. However, conventional analog computing is …

In recent years, hyperspectral image processing has expanded beyond traditional remote
sensing and military applications to include civilian domains like industrial quality control …

An artificial neural network is very important to the design and analysis of any complex
algorithm and process. In this paper, a photonic artificial neuron is designed using Arduino …

Photonic integrated circuits play an important role in the field of optical computing, promising
faster and more energy-efficient operations compared to their digital counterparts. This …

As photonic technologies continue to grow in multidimensional aspects, integrated
photonics holds a unique position and continuously presents enormous possibilities to …