Results 11 to 20 of about 1,404,609 (276)

Not All Electrode Channels Are Needed: Knowledge Transfer From Only Stimulated Brain Regions for EEG Emotion Recognition

open access: yesFrontiers in Neuroscience, 2022
Emotion recognition from affective brain-computer interfaces (aBCI) has garnered a lot of attention in human-computer interactions. Electroencephalographic (EEG) signals collected and stored in one database have been mostly used due to their ability to ...
Hayford Perry Fordson   +4 more
doaj   +1 more source

A Channel Selection Method for Emotion Recognition From EEG Based on Swarm-Intelligence Algorithms

open access: yesIEEE Access, 2021
Increasing demand for human-computer interaction applications has escalated the need for automatic emotion recognition as emotions are essential for natural communication.
Esen Yildirim, Yasin Kaya, Fatih Kilic
doaj   +1 more source

A QoE-Based Framework for Video Streaming Over LTE-Unlicensed

open access: yesIEEE Access, 2020
To improve the system capacity and accommodate the ever-increasing demand for bandwidth by the network users, LTE service providers have turned their attention to the unlicensed industrial, scientific, and medical (ISM) spectrum; currently heavily ...
Mohamed S. Hassan   +4 more
doaj   +1 more source

Enhancing Classification Performance of fNIRS-BCI by Identifying Cortically Active Channels Using the z-Score Method

open access: yesSensors, 2020
A state-of-the-art brain–computer interface (BCI) system includes brain signal acquisition, noise removal, channel selection, feature extraction, classification, and an application interface. In functional near-infrared spectroscopy-based BCI (fNIRS-BCI)
Hammad Nazeer   +6 more
doaj   +1 more source

Deep learning-based self-induced emotion recognition using EEG

open access: yesFrontiers in Neuroscience, 2022
Emotion recognition from electroencephalogram (EEG) signals requires accurate and efficient signal processing and feature extraction. Deep learning technology has enabled the automatic extraction of raw EEG signal features that contribute to classifying ...
Yerim Ji, Suh-Yeon Dong
doaj   +1 more source

A Deep Neural Network-Based Spike Sorting With Improved Channel Selection and Artefact Removal

open access: yesIEEE Access, 2023
In order to implement highly efficient brain-machine interface (BMI) systems, high-channel count sensing is often used to record extracellular action potentials.
Christian O. Okreghe   +2 more
doaj   +1 more source

A game-theoretic approach to select a channel for supplying required materials in producing a product manufactured from recyclables [PDF]

open access: yesتصمیم گیری و تحقیق در عملیات, 2023
Purpose: In this research, a recyclable waste is used to manufacture a specific product. For this reason, a supply chain is considered containing manufacturer, recycler, and waste warehouse.
Hamed Jafari
doaj   +1 more source

Channel Selection Using Gumbel Softmax [PDF]

open access: yes, 2020
ECCV ...
Charles Herrmann   +2 more
openaire   +2 more sources

Software Usability Testing Using EEG-Based Emotion Detection and Deep Learning

open access: yesSensors, 2023
It is becoming increasingly attractive to detect human emotions using electroencephalography (EEG) brain signals. EEG is a reliable and cost-effective technology used to measure brain activities.
Sofien Gannouni   +4 more
doaj   +1 more source

Magnesium Selective Ion Channels [PDF]

open access: yesBiophysical Journal, 2007
The homeostasis of intracellular ion concentrations within physiological limits is one fundamental characteristic of any living organism. Magnesium, an alkaline earth metal, is well known to stabilize macromolecule structure and to participate as an essential cofactor in many enzymatic reactions.
openaire   +2 more sources

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