Event data classification

7 papers with code • 3 benchmarks • 3 datasets

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Most implemented papers

A predictive model for the identification of learning styles in MOOC environments

hclon/Learning-Styles-prediction 12 Oct 2019

Massive online open course (MOOC) platform generates a large amount of data, which provides many opportunities for studying the behaviors of learners.

Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction

aa-samad/conv_snn 27 Mar 2020

Spiking neural networks (SNNs) can be used in low-power and embedded systems (such as emerging neuromorphic chips) due to their event-based nature.

Neuromorphic Data Augmentation for Training Spiking Neural Networks

intelligent-computing-lab-yale/nda_snn 11 Mar 2022

In an effort to minimize this generalization gap, we propose Neuromorphic Data Augmentation (NDA), a family of geometric augmentations specifically designed for event-based datasets with the goal of significantly stabilizing the SNN training and reducing the generalization gap between training and test performance.

A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks

sunhongze/STL-SNN 10 Jun 2022

Most existing methods for training SNNs are based on the concept of synaptic plasticity; however, learning in the realistic brain also utilizes intrinsic non-synaptic mechanisms of neurons.

Ecsnet: Spatio-temporal feature learning for event camera

happychenpipi/ECSNet IEEE Transactions on Circuits and Systems for Video Technology 2022

To fully exploit their inherent sparsity with reconciling the spatio-temporal information, we introduce a compact event representation, namely 2D-1T event cloud sequence (2D-1T ECS).

Online Training Through Time for Spiking Neural Networks

pkuxmq/ottt-snn 9 Oct 2022

With OTTT, it is the first time that two mainstream supervised SNN training methods, BPTT with SG and spike representation-based training, are connected, and meanwhile in a biologically plausible form.

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

event-ahu/agcn_event_classification 8 Jun 2023

To address these issues, we propose a novel dual point-voxel absorbing graph representation learning for event stream data representation.