8 citations · 8 across the 6 of their papers we have counts for
6 papers
Amicable Aid: Perturbing Images to Improve Classification Performance
Juyeop Kim, Jun-Ho Choi, Soobeom Jang +1
While adversarial perturbation of images to attack deep image classification models pose serious security concerns in practice, this paper suggests a novel paradigm where the conce…
EEG-based Emotional Video Classification via Learning Connectivity Structure
Soobeom Jang, Seong-Eun Moon, Jong-Seok Lee
Electroencephalography (EEG) is a useful way to implicitly monitor the users perceptual state during multimedia consumption. One of the primary challenges for the practical use of…
On Evaluating Perceptual Quality of Online User-Generated Videos
Soobeom Jang, Jong-Seok Lee
This paper deals with the issue of the perceptual quality evaluation of user-generated videos shared online, which is an important step toward designing video-sharing services that…
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…