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EEG-Based Emotion Recognition Using Regularized Graph Neural Networks [PDF]
IEEE Transactions on Affective Computing, 2020 Electroencephalography (EEG) measures the neuronal activities in different brain regions via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit the topology of EEG channels.
Miao, Chunyan, Wang, Di, Zhong, Peixiang
core +2 more sources
EEG Based Emotion Recognition: A Tutorial and Review [PDF]
ACM Computing Surveys, 2022 Emotion recognition technology through analyzing the EEG signal is currently an essential concept in Artificial Intelligence and holds great potential in emotional health care, human-computer interaction, multimedia content recommendation, etc.
Xiang Li +8 more
semanticscholar +1 more source
Energies, 2021 To ensure broad application of renewable and energy-efficient energy systems in buildings and neighborhoods, profitable business models are vital. Energy supply contracting helps building residents to overcome the barrier of high upfront investment costs
Carolin Monsberger +2 more
doaj +1 more source
Energies, 2022 Given the ongoing transformation of the transport sector toward electrification, expansion of the current charging infrastructure is essential to meet future charging demands.
Antonia Golab +2 more
doaj +1 more source
Deep learning with convolutional neural networks for EEG decoding and visualization [PDF]
Human Brain Mapping, 2017 Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data.
R. Schirrmeister +8 more
semanticscholar +1 more source
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces [PDF]
Journal of Neural Engineering, 2016 Objective. Brain–computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI
Vernon J. Lawhern +5 more
semanticscholar +1 more source
Frontiers in Behavioral Neuroscience, 2021 To explore brain function using functional connectivity and network topology derived from electroencephalogram (EEG) in patients with pharmacoresistant epileptic encephalopathy with cannabidiol as adjunctive antiepileptic treatment.
Lilia Maria Morales Chacón +4 more
doaj +1 more source
EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization
IEEE transactions on neural systems and rehabilitation engineering, 2022 Due to the limited perceptual field, convolutional neural networks (CNN) only extract local temporal features and may fail to capture long-term dependencies for EEG decoding.
Yonghao Song +3 more
semanticscholar +1 more source
Efficient Load Management for BEV Charging Infrastructure in Multi-Apartment Buildings
Energies, 2020 Interest in and demand for battery electric vehicles (BEVs) is growing strongly due to the increasing awareness of climate change and specific decarbonization goals.
Jasmine Ramsebner +2 more
doaj +1 more source
Impact of Different Charging Strategies for Electric Vehicles in an Austrian Office Site
Energies, 2020 Electric vehicles represent a necessary alternative for wheeled transportation to meet the global and national targets specified in the Paris Agreement of 2016.
Carlo Corinaldesi +4 more
doaj +1 more source