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 …

Remarkable technological developments for efficient image recognition (ie, image
acquisition and image data processing) have been reported in the past decade. Such …

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 …

Compared to human vision, conventional machine vision composed of an image sensor and
processor suffers from high latency and large power consumption due to physically …

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in
3 keywords: smaller, faster, and smarter.(1) Smaller: Devices are becoming more compact …

Convolutional Neural Networks (CNN) are a class of machine learning models
predominately used in computer vision tasks and can achieve human-like performance …

Brain-inspired electronics represent a promising paradigm to resolve the energy and time
bottlenecks in conventional digital machines. Recent advances have spanned both …

Neuromorphic visual system with image perception, memory, and preprocessing functions is
expected to simulate basic features of the human retina. Organic optoelectronic synaptic …

Emulating the biological visual perception system typically requires a complex architecture
including the integration of an artificial retina and optic nerves with various synaptic …

The paper reviews the progress of neuromorphic vision chip research in decades. It focuses
on two kinds of the neuromorphic vision chips: frame-driven (FD) and event-driven (ED) …