Dynamic Spatiotemporal Pattern Recognition with Recurrent Spiking Neural Network

Keyphrases

• Spiking Neurons 100%
• Recurrent Spiking Neural Networks 100%
• Temporal Action Detection 100%
• Spatiotemporal Pattern 66%
• Spatiotemporal Dynamics 66%
• Spike Latency 66%
• Activity Patterns 33%
• Encoder 33%
• Pattern Recognition 33%
• Recognition-based 33%
• Decoder 33%
• Learning Algorithm 33%
• Recognition Task 33%
• Everyday Life 33%
• Result-oriented 33%
• Backpropagation 33%
• Extracting Information 33%
• Test Accuracy 33%
• Temporal Difference 33%
• Spiking Activity 33%
• Output Neurons 33%
• Neural Computation 33%
• Spiking Neural Networks 33%
• Rapid Recognition 33%
• Human Action 33%
• Output Layer 33%
• Spike Count 33%
• Hidden Layer 33%
• Image Classification 33%
• Neuronal Processing 33%
• Static Patterns 33%
• Spike-based 33%
• Retinal Neurons 33%
• Input Layer 33%
• Transmission Delay 33%
• Connected Neurons 33%
• Brain Activity Patterns 33%
• Decoding Process 33%
• Neuromorphic Computing 33%
• 3D Trajectory 33%
• Cascaded Network 33%
• Dynamic Brain Activity 33%
• Static Features 33%

Computer Science

• Pattern Recognition 100%
• Neural Network 100%
• Learning Algorithm 33%
• Neural Network Model 33%
• Neural Computation 33%
• Extract Information 33%
• Brain Activity 33%
• Image Classification 33%
• Real-Time Action 33%
• Transmission Delay 33%
• Decoding Process 33%
• temporal difference 33%