Advancements in affective disorder detection: Using multimodal physiological signals and neuromorphic computing based on snns
Currently, the integration of artificial intelligence (AI) techniques with multimodal
physiological signals represents a pivotal approach to detect affective disorders (ADs). With …
physiological signals represents a pivotal approach to detect affective disorders (ADs). With …
Are Conventional SNNs Really Efficient? A Perspective from Network Quantization
Abstract Spiking Neural Networks (SNNs) have been widely praised for their high energy
efficiency and immense potential. However comprehensive research that critically contrasts …
efficiency and immense potential. However comprehensive research that critically contrasts …
FireFly-S: Exploiting Dual-Side Sparsity for Spiking Neural Networks Acceleration With Reconfigurable Spatial Architecture
Spiking Neural Networks (SNNs), with their brain-inspired structure using discrete spikes
instead of continuous activations, are gaining attention for their potential of efficient …
instead of continuous activations, are gaining attention for their potential of efficient …
Revealing Untapped DSP Optimization Potentials for FPGA-Based Systolic Matrix Engines
Systolic architectures are widely embraced by neural network accelerators for their superior
performance in highly parallelized computation. The DSP48E2s serve as dedicated …
performance in highly parallelized computation. The DSP48E2s serve as dedicated …