A spiking neural network (SNN) inspired by the structure and principles of the human brain
can significantly enhance the energy efficiency of artificial intelligence computing by …

Artificial neuronal devices are critical building blocks of neuromorphic computing systems
and currently the subject of intense research motivated by application needs from new …

Optoelectronic synapses integrating synaptic and optical-sensing functions exhibit large
advantages in neuromorphic computing for visual information processing and complex …

A neuromorphic module of an electronic nose (E‐nose) is demonstrated by hybridizing a
chemoresistive gas sensor made of a semiconductor metal oxide (SMO) and a single …

The development of artificial intelligence has posed a challenge to machine vision based on
conventional complementary metal‐oxide semiconductor (CMOS) circuits owing to its high …

The cone photoreceptors in our eyes selectively transduce the natural light into spiking
representations, which endows the brain with high energy-efficiency color vision. However …

Inspired by the principles of the biological nervous system, neuromorphic engineering has
brought a promising alternative approach to intelligence computing with high energy …

A novel biomimicked neuromorphic sensor for an energy efficient and highly scalable
electronic tongue (E-tongue) is demonstrated with a metal-oxide-semiconductor field-effect …

The traditional von Neumann architecture is gradually failing to meet the urgent need for
highly parallel computing, high-efficiency, and ultra-low power consumption for the current …

By mimicking the behavior of the human brain, artificial neural systems offer the possibility to
further improve computing efficiency and solve the von Neumann bottleneck. In particular …