TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks
29TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE, ASP-DAC 2024（2024）
关键词
Neural Network,Spiking Activity,Spiking Neural Networks,Adaptive Spiking,Time Step,Artificial Neural Network,Energy Efficiency,Number Of Steps,Temporal Information,Number Of Time Steps,Processing Latency,Multiple Time Steps,Deep Artificial Neural Networks,Energy Consumption,Time Window,Differential Levels,Temporal Dimension,Regularization Term,Accuracy Loss,Small Window,Spike Trains,Spike Firing,Firing Time,Spike Count,Input Spike,Output Spike,Synaptic Weights,Forward Pass,ImageNet Dataset,Accuracy Of Network
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要