Imagen de Portada

MC-QDSNN: Quantized Deep evolutionary SNN with Multi-Dendritic Compartment Neurons for Stress Detection using Physiological Signals

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	S, Ajay B, K, Phani Pavan, Rao, Madhav
Formato:	Preprint
Publicado:	2024
Materias:	Neural and Evolutionary Computing Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Optimal ANN-SNN Conversion with Group Neurons
por: Lv, Liuzhenghao, et al.
Publicado: (2024)

Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning
por: Sun, Yinqian, et al.
Publicado: (2025)

Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
por: Oh, Hyunseok, et al.
Publicado: (2024)

Efficient Online Learning for Networks of Two-Compartment Spiking Neurons
por: Yin, Yujia, et al.
Publicado: (2024)

MD-SNN: Membrane Potential-aware Distillation on Quantized Spiking Neural Network
por: Lee, Donghyun, et al.
Publicado: (2025)

TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling
por: Zhang, Shimin, et al.
Publicado: (2023)

An Asynchronous Multi-core Accelerator for SNN inference
por: Chen, Zhuo, et al.
Publicado: (2024)

One-Timestep is Enough: Achieving High-performance ANN-to-SNN Conversion via Scale-and-Fire Neurons
por: Chen, Qiuyang, et al.
Publicado: (2025)

ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization
por: Tang, Kaiwen, et al.
Publicado: (2026)

Multi-objective evolutionary GAN for tabular data synthesis
por: Ran, Nian, et al.
Publicado: (2024)

BrainTransformers: SNN-LLM
por: Tang, Zhengzheng, et al.
Publicado: (2024)

Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection
por: Liao, Jing-Xiao, et al.
Publicado: (2022)

Towards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization
por: Wang, Ziming, et al.
Publicado: (2022)

NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification
por: Zhang, Chuhan, et al.
Publicado: (2023)

Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons
por: Ghoreishee, Aref, et al.
Publicado: (2025)

Efficient ANN-SNN Conversion with Error Compensation Learning
por: Liu, Chang, et al.
Publicado: (2025)

Scalable Superconductor Neuron with Ternary Synaptic Connections for Ultra-Fast SNN Hardware
por: Karamuftuoglu, Mustafa Altay, et al.
Publicado: (2024)

Balanced Resonate-and-Fire Neurons
por: Higuchi, Saya, et al.
Publicado: (2024)

SkipSNN: Efficiently Classifying Spike Trains with Event-attention
por: Yin, Hang, et al.
Publicado: (2024)

Improving Low-Latency Learning Performance in Spiking Neural Networks via a Change-Perceptive Dendrite-Soma-Axon Neuron
por: Huang, Zeyu, et al.
Publicado: (2025)

SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks
por: Venkatesh, Sreyes, et al.
Publicado: (2024)

Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures
por: Sanaullah, et al.
Publicado: (2024)

Understanding the Convergence in Balanced Resonate-and-Fire Neurons
por: Higuchi, Saya, et al.
Publicado: (2024)

Asynchronous Bioplausible Neuron for SNN for Event Vision
por: Kachole, Sanket, et al.
Publicado: (2023)

Scalable Dendritic Modeling Advances Expressive and Robust Deep Spiking Neural Networks
por: Huang, Yifan, et al.
Publicado: (2024)

MOELIGA: a multi-objective evolutionary approach for feature selection with local improvement
por: Vignolo, Leandro, et al.
Publicado: (2026)

Reservoir Computation with Networks of Differentiating Neuron Ring Oscillators
por: Yeung, Alexander, et al.
Publicado: (2025)

CHNNet: An Artificial Neural Network With Connected Hidden Neurons
por: Shahir, Rafiad Sadat, et al.
Publicado: (2023)

ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network
por: Xu, Shang, et al.
Publicado: (2025)

CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
por: Huang, Yongsheng, et al.
Publicado: (2025)

Skewed Neuronal Heterogeneity Enhances Efficiency On Various Computing Systems
por: Golmohammadi, Arash, et al.
Publicado: (2024)

Memory-DD: A Low-Complexity Dendrite-Inspired Neuron for Temporal Prediction Tasks
por: Yang, Dongjian, et al.
Publicado: (2025)

SNNF: An SNN-based Near-Sensor Noise Filter for Dynamic Vision Sensors
por: Yang, Yahan, et al.
Publicado: (2026)

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
por: Lee, Donghyun, et al.
Publicado: (2024)

MorphSNN: Adaptive Graph Diffusion and Structural Plasticity for Spiking Neural Networks
por: Huang, Yongsheng, et al.
Publicado: (2026)

On Accelerating Deep Neural Network Mutation Analysis by Neuron and Mutant Clustering
por: Lyons, Lauren, et al.
Publicado: (2025)

Toward Efficient Deep Spiking Neuron Networks:A Survey On Compression
por: Xie, Hui, et al.
Publicado: (2024)

Bio-Inspired Adaptive Neurons for Dynamic Weighting in Artificial Neural Networks
por: Islam, Ashhadul, et al.
Publicado: (2024)

A More Accurate Approximation of Activation Function with Few Spikes Neurons
por: Jeong, Dayena, et al.
Publicado: (2024)

Adversarial attacks to image classification systems using evolutionary algorithms
por: Nesmachnow, Sergio, et al.
Publicado: (2025)