Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …

Neuromorphic electronics have great potential in the emulation of the sensory, cognitive, self-
learning, and actuating functions of robots. While typically implemented in rigid silicon …

This paper updates the survey of AI accelerators and processors from past three years. This
paper collects and summarizes the current commercial accelerators that have been publicly …

The field of Deep Learning (DL) has seen a remarkable series of developments with
increasingly accurate and robust algorithms. However, the increase in performance has …

Develo** neuromorphic intelligence on event-based datasets with Spiking Neural
Networks (SNNs) has recently attracted much research attention. However, the limited size …

Abstract The combination of Spiking Neural Networks (SNNs) and Transformers has
attracted significant attention due to their potential for high energy efficiency and high …

The brain possesses the remarkable ability to seamlessly integrate perception with decision
making within a dynamically changing environment in a fault-tolerant, end-to-end manner …

For vehicles to navigate autonomously, they need to perceive and understand their
immediate surroundings. Currently, cameras are the preferred sensors, due to their high …

Spiking neural networks (SNNs) offer an energy-efficient alternative to conventional deep
learning by emulating the event-driven processing manner of the brain. Incorporating …

The security and privacy concerns along with the amount of data that is required to be
processed on regular basis has pushed processing to the edge of the computing systems …