The training of multilayer spiking neural networks (SNNs) using the error backpropagation
algorithm has made significant progress in recent years. Among the various training …

Recently, artificial intelligence (AI)-based algorithms have revolutionized the medical image
segmentation processes. Thus, the precise segmentation of organs and their lesions may …

Spiking neural networks (SNNs) are attracting widespread interest due to their biological
plausibility, energy efficiency, and powerful spatiotemporal information representation …

For a long time, biology and neuroscience fields have been a great source of inspiration for
computer scientists, towards the development of Artificial Intelligence (AI) technologies. This …

Spiking neural networks (SNNs) are considered an attractive option for edge-side
applications due to their sparse, asynchronous and event-driven characteristics. However …

Abstract Automatic Lip-Reading (ALR) requires the recognition of spoken words based on a
visual recording of the speaker's lips without access to the sound. ALR with neuromorphic …

Lip reading is a visual alternative to enhance the intelligence of traditional speech
recognition, which can benefit from retina-like event cameras that focus on dynamic …

Spiking neural networks (SNNs) are well-suited for neuromorphic hardware due to their
biological plausibility and energy efficiency. These networks utilize sparse, asynchronous …

This paper presents a digital edge neuromorphic spiking neural network (SNN) processor
chip for a variety of edge intelligent cognitive applications. This processor allows high …

Motor imagery, an important category in electroencephalogram (EEG) research, often
intersects with scenarios demanding low energy consumption, such as portable medical …