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SOTA
Audio Classification
Audio Classification On Ssc
Audio Classification On Ssc
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
Event-SSM
88.4
Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models
SNN with Dilated Convolution with Learnable Spacings
80.69
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
RadLIF
77.4
A surrogate gradient spiking baseline for speech command recognition
SpikGRU
77
Investigating current-based and gating approaches for accurate and energy-efficient spiking recurrent neural networks
Adaptive SRNN
74.2
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
0 of 5 row(s) selected.
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Next
HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Audio Classification
Audio Classification On Ssc
Audio Classification On Ssc
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
Paper Title
Event-SSM
88.4
Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models
SNN with Dilated Convolution with Learnable Spacings
80.69
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
RadLIF
77.4
A surrogate gradient spiking baseline for speech command recognition
SpikGRU
77
Investigating current-based and gating approaches for accurate and energy-efficient spiking recurrent neural networks
Adaptive SRNN
74.2
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
0 of 5 row(s) selected.
Previous
Next
Audio Classification On Ssc | SOTA | HyperAI