no code implementations • 3 Jul 2023 • Gabriel Tjio, Ping Liu, Yawei Luo, Chee Keong Kwoh, Joey Zhou Tianyi
Our workflow generates target-like images using the noisy predictions from the original target domain images.
no code implementations • 29 Sep 2021 • Zhuoyi Lin, Biao Ye, Xu He, Shuo Sun, Rundong Wang, Rui Yin, Xu Chi, Chee Keong Kwoh
A machine learning system is typically composed of model and data.
1 code implementation • 26 Jun 2021 • Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, XiaoLi Li, Cuntai Guan
In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabeled data.
Ranked #1 on Recognizing And Localizing Human Actions on HAR
Automatic Sleep Stage Classification Contrastive Learning +9
no code implementations • 28 Jul 2020 • Zhuoyi Lin, Lei Feng, Xingzhi Guo, Yu Zhang, Rui Yin, Chee Keong Kwoh, Chi Xu
In this paper, we propose a novel representation learning-based model called COMET (COnvolutional diMEnsion inTeraction), which simultaneously models the high-order interaction patterns among historical interactions and embedding dimensions.
1 code implementation • 19 Jul 2020 • Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiao-Li Li
Thirdly, an empirical analysis is conducted to evaluate the performance of the selected methods across seven diseases.
3 code implementations • 17 May 2020 • Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiao-Li Li
Real-world networks often exist with multiple views, where each view describes one type of interaction among a common set of nodes.