Search Results for author: Soobeom Jang

Found 5 papers, 1 papers with code

Amicable Aid: Perturbing Images to Improve Classification Performance

no code implementations9 Dec 2021 Juyeop Kim, Jun-Ho Choi, Soobeom Jang, Jong-Seok Lee

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 concept of image perturbation can benefit classification performance, which we call amicable aid.

Adversarial Attack Classification +2

EEG-based Emotional Video Classification via Learning Connectivity Structure

1 code implementation28 May 2019 Soobeom Jang, Seong-Eun Moon, Jong-Seok Lee

Electroencephalography (EEG) is a useful way to implicitly monitor the users perceptual state during multimedia consumption.

Classification EEG +3

EEG-based video identification using graph signal modeling and graph convolutional neural network

no code implementations12 Sep 2018 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.

EEG Electroencephalogram (EEG)

Evaluation of Preference of Multimedia Content using Deep Neural Networks for Electroencephalography

no code implementations11 Sep 2018 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.

EEG Electroencephalogram (EEG)

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