spiking neural network
PulseAugur coverage of spiking neural network — every cluster mentioning spiking neural network across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
-
New DBHN-Net cuts speech enhancement complexity 7.5x
Researchers have developed a new Dual-Branch Hybrid Neural Network (DBHN-Net) designed to significantly reduce the computational complexity and power consumption of speech enhancement systems. The network integrates tra…
-
New LoRSP framework uses spiking neurons for sparse visual prompts
Researchers have developed a novel framework called LoRSP, which integrates brain-inspired spiking neural networks with low-rank factorization for visual prompting. This approach generates sparse, instance-specific prom…
-
ELSA architecture enables elastic inference for efficient neuromorphic computing
Researchers have introduced ELSA, a novel architecture designed to enhance the efficiency of Spiking Neural Networks (SNNs) for neuromorphic computing. ELSA addresses limitations in existing accelerators by enabling tru…
-
New compute-in-memory macro boosts edge AI inference efficiency
Researchers have developed E-ReCON, a novel compute-in-memory (CIM) macro designed for efficient AI inference on edge devices. This macro utilizes a compact ReRAM bitcell capable of performing multiplication for both co…
-
AI safety thresholds reinterpreted as neuron spiking thresholds
Researchers have proposed a new method for evaluating safety in automated driving systems by modeling safety thresholds as neuron spiking thresholds. This approach uses a spiking neural network (SNN) trained on human br…
-
Ferroelectric synapses enable personalized SNNs for EEG signal processing
Researchers have developed personalized spiking neural networks (SNNs) utilizing ferroelectric synapses for processing electroencephalography (EEG) signals. This approach aims to improve the generalization of brain-comp…