activity
20172021
most citedEmbraceNet: A robust deep learning architecture for multimodal classification

148 citations · 283 across the 7 of their papers we have counts for

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eess.SP2020★ 17 cited

EmbraceNet for Activity: A Deep Multimodal Fusion Architecture for Activity Recognition

Jun-Ho Choi, Jong-Seok Lee

Human activity recognition using multiple sensors is a challenging but promising task in recent decades. In this paper, we propose a deep multimodal fusion model for activity recog…

eess.SP2018

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…