94 citations · 94 across the 1 of their papers we have counts for
6 papers
Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks
Seong-Eun Moon, Chun-Jui Chen, Cho-Jui Hsieh +2
Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usuall…
Perceptual Experience Analysis for Tone-mapped HDR Videos based on EEG and Peripheral Physiological Signals
Seong-Eun Moon, Jong-Seok Lee
High dynamic range (HDR) imaging has been attracting much attention as a technology that can provide immersive experience. Its ultimate goal is to provide better quality of experie…
Implicit Analysis of Perceptual Multimedia Experience Based on Physiological Response: A Review
Seong-Eun Moon, Jong-Seok Lee
The exponential growth of popularity of multimedia has led to needs for user-centric adaptive applications that manage multimedia content more effectively. Implicit analysis, which…
EEG-based video identification using graph signal modeling and graph convolutional neural network
Soobeom Jang, Seong-Eun Moon, Jong-Seok Lee
This paper proposes a novel graph signal-based deep learning method for electroencephalography (EEG) and its application to EEG-based video identification. We present new methods t…
Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information
Seong-Eun Moon, Soobeom Jang, Jong-Seok Lee
Emotion recognition based on electroencephalography (EEG) has received attention as a way to implement human-centric services. However, there is still much room for improvement, pa…
Evaluation of Preference of Multimedia Content using Deep Neural Networks for Electroencephalography
Seong-Eun Moon, Soobeom Jang, Jong-Seok Lee
Evaluation of quality of experience (QoE) based on electroencephalography (EEG) has received great attention due to its capability of real-time QoE monitoring of users. However, it…