Artificial neural networks (ANNs) have experienced a rapid advancement for their success in
various application domains, including autonomous driving and drone vision. Researchers …

Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient
diagnosis. Due to this composite cell, the conceptual classifications differ from each and …

Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …

Spiking Neural Network (SNN), the next generation of Neural Network, is supposed to be
more energy-saving than the previous generation represented by Convolution Neural …

Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge
devices is still challenging. Unlike the most state of the art inference engines which are …

Artificial Neural Networks (ANNs) show great performance in several data analysis tasks
including visual and auditory applications. However, direct implementation of these …

The traditional neural network Intelligent chip has the problem of high power consumption
due to classical computing architecture, limiting the development of neural network …

Vision processing with dynamic vision sensors (DVSs) is becoming increasingly popular.
This type of a bio-inspired vision sensor does not record static images. The DVS pixel …

Spiking Neural Networks (SNNs) can be configured to produce almost-equivalent accurate
Analog Neural Networks (ANNs) by various ANN-SNN conversion methods. Most of these …

Event-based vision, led by a dynamic vision sensor (DVS), is a bio-inspired vision model
that leverages timestamped pixel-level brightness changes of non-static scenes. Thus …