Results 21 to 30 of about 251 (118)

Online Traffic Accident Spatial‐Temporal Post‐Impact Prediction Model on Highways Based on Spiking Neural Networks

Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021
Traffic accident management as an approach to improve public security and reduce economic losses has received public attention for a long time, among which traffic accidents post‐impact prediction (TAPIP) is one of the most important procedures. However, existing systems and methodologies for TAPIP are insufficient for addressing the problem.
Duowei Li, Jianping Wu, Depin Peng, Alain Lambert   +3 more
wiley   +1 more source

Navigation Learning Assessment Using EEG-Based Multi-Time Scale Spatiotemporal Compound Model

IEEE Transactions on Neural Systems and Rehabilitation Engineering
This study presents a novel method to assess the learning effectiveness using Electroencephalography (EEG)-based deep learning model. It is difficult to assess the learning effectiveness of professional courses in cultivating students’ ability ...
Lingling Wang, Yixin Liu, Yiqing Li, Renxiang Chen, Xiaohong Liu, Li Fu, Yao Wang   +6 more
doaj   +1 more source

Modeling functional brain connections in methamphetamine and opioid abusers

Medicine in Novel Technology and Devices
Substance abuse has become a significant problem worldwide. The primary purpose of this study was to model the functional brain connectivity in methamphetamines (Meth) and opioids (Op) groups in comparison with the healthy control (HC) group.
Nasimeh Marvi, Javad Haddadnia, Mohammad Reza Fayyazi Bordbar   +2 more
doaj   +1 more source

Transfer Learning of Fuzzy Spatio-Temporal Rules in the NeuCube Brain-Inspired Spiking Neural Network: A Case Study on EEG Spatio-temporal Data:A Case Study on Spatio-Temporal Brain Data [PDF]

, 2023
The article demonstrates for the first time that a brain-inspired spiking neural network (SNN) architecture can be used not only to learn spatio-temporal data, but also to extract fuzzy spatio-temporal rules from such data and to update these rules ...
Goh, Wilson, Doborjeh, Maryam, Kasabov, Nikola, Tu, Enmei, Yang, Jie, Tan, Yongyao, Lee, Jimmy   +6 more
core   +1 more source

Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach

Big Data and Cognitive Computing
The transfer of learning (TL) is the process of applying knowledge and skills learned in one context to a new and different context. Efficient use of memory is essential in achieving successful TL and good learning outcomes.
Mojgan Hafezi Fard, Krassie Petrova, Nikola Kirilov Kasabov, Grace Y. Wang   +3 more
doaj   +1 more source

Studying Transfer of Learning using a Brain-Inspired Spiking Neural Network in the Context of Learning a New Programming Language [PDF]

, 2021
Transfer of learning (TL) has been an important research area for scholars, educators, and cognitive psychologists for over a century. However, it is not yet understood why applying existing knowledge and skills in a new context does not always follow ...
Fard, M, Petrova, K, Petrova, Krassie, Fard, Mojgan Hafezi, Wang, G, Fard, Mojgan, Kasabov, Nikola, Kasabov, N, Wang, Grace Y., Wang, Grace, Mojgan Hafezi Fard, Nikola Kasabov, Grace Y. Wang, Krassie Petrova   +13 more
core   +1 more source

An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks [PDF]

, 2017
This research study proposes a novel method of inter-related problems in face recognition using the NeuCube neuromorphic computational platform. We investigated age classification and gender recognition.
Fahad Bashir Alvi, Kasabov, Nikola, Russel Pears, Alvi, Fahad, Pears, Russel, Nikola Kasabov   +5 more
core   +1 more source

A Framework for the Integration of the Emotiv EEG System into the NeuCube Spiking Neural Network Environment for Robotics Control

, 2015
As BCI has been widely studied in recent years, lots of BCI applications have been de-veloped. In this thesis, to implement BCI into individual devices is simulated by con-trolling a robot.
Wang, Jianfei
core   +1 more source

Corridor scene recognition for mobile robots based on multi-sonar-sensor information and NeuCube

, 2015
为提高室内移动机器人的环境感知能力,针对其常处的结构化走廊场景的分类、Spiking神经网络(SNN)和基于SNN的新型计算模型NeuCube进 行研究。SNN利用尖脉冲传递时、空信息,比传统的神经网络更适于动态、时序信息的分析,以及各种模式信息的识别和分类。此外,SNN更易于用硬件实现。 在对NeuCube的基本原理、学习方法和计算步骤进行讨论的基础上,利用多超声传感信息和NeuCube对室内移动机器人常处的7种走廊场景进行识别 ...
王永吉, 谭民, 曾慧, 侯增广, 潘世英, 王秀青   +5 more
core  

Transfer Learning of Fuzzy Spatio-Temporal Rules in the NeuCube Brain-Inspired Spiking Neural Network: A Case Study on EEG Spatio-temporal Data

, 2023
<p>EEG data collected from several subjects when perfoming complex spatio-temporal tasks </p>
Nikola Kasabov, Yongyao Tan Tan, Maryam Doborjeh, Enmei Tu, Jie Yang   +4 more
openaire   +1 more source