Search Results for author: Shibo Zhou

Found 7 papers, 1 papers with code

Spectrum Attention Mechanism for Time Series Classification

no code implementations25 Jan 2021 Shibo Zhou, Yu Pan

Since time series always contains a lot of noise, which has a negative impact on network training, people usually filter the original data before training the network.

Classification General Classification +3

A Spike Learning System for Event-driven Object Recognition

no code implementations21 Jan 2021 Shibo Zhou, Wei Wang, Xiaohua LI, Zhanpeng Jin

The proposed temporal coding scheme maps each event's arrival time and data into SNN spike time so that asynchronously-arrived events are processed immediately without delay.

Object Object Recognition

Spiking Neural Networks with Single-Spike Temporal-Coded Neurons for Network Intrusion Detection

no code implementations15 Oct 2020 Shibo Zhou, Xiaohua LI

To support this claim, we show that SNNs built with nonleaky neurons can have a less-complex and less-nonlinear input-output response.

Network Intrusion Detection

Temporal Pulses Driven Spiking Neural Network for Fast Object Recognition in Autonomous Driving

no code implementations24 Jan 2020 Wei Wang, Shibo Zhou, Jingxi Li, Xiaohua LI, Junsong Yuan, Zhanpeng Jin

Accurate real-time object recognition from sensory data has long been a crucial and challenging task for autonomous driving.

Autonomous Driving Object +1

Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data

no code implementations17 Dec 2019 Shibo Zhou, Ying Chen, Xiaohua LI, Arindam Sanyal

In this paper, we integrate spiking convolutional neural network (SCNN) with temporal coding into the YOLOv2 architecture for real-time object detection.

3D Object Detection object-detection +2

Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

1 code implementation24 Sep 2019 Shibo Zhou, Xiaohua LI, Ying Chen, Sanjeev T. Chandrasekaran, Arindam Sanyal

Spiking neural network (SNN) is interesting both theoretically and practically because of its strong bio-inspiration nature and potentially outstanding energy efficiency.

Data Augmentation Object Recognition

Object Detection based on LIDAR Temporal Pulses using Spiking Neural Networks

no code implementations29 Oct 2018 Shibo Zhou, Wei Wang

Neural networks has been successfully used in the processing of Lidar data, especially in the scenario of autonomous driving.

Autonomous Driving Benchmarking +3

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