36 citations · 55 across the 7 of their papers we have counts for
8 papers
Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen +3
The past few years have witnessed a remarkable advance in deep learning for EEG-based sleep stage classification (SSC). However, the success of these models is attributed to posses…
A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
Zhenghua Chen, Min Wu, Alvin Chan +2
Artificial Intelligence (AI) is a fast-growing research and development (R&D) discipline which is attracting increasing attention because of its promises to bring vast benefits for…
Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment
Yuecong Xu, Jianfei Yang, Haozhi Cao +4
Multi-Source Domain Adaptation (MSDA) is a more practical domain adaptation scenario in real-world scenarios. It relaxes the assumption in conventional Unsupervised Domain Adaptati…
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network
Yuecong Xu, Jianfei Yang, Haozhi Cao +3
Partial Domain Adaptation (PDA) is a practical and general domain adaptation scenario, which relaxes the fully shared label space assumption such that the source label space subsum…
Time-Series Representation Learning via Temporal and Contextual Contrasting
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen +4
Learning decent representations from unlabeled time-series data with temporal dynamics is a very challenging task. In this paper, we propose an unsupervised Time-Series representat…
Deep Inertial Odometry with Accurate IMU Preintegration
Rooholla Khorrambakht, Chris Xiaoxuan Lu, Hamed Damirchi +2
Inertial Measurement Units (IMUs) are interceptive modalities that provide ego-motion measurements independent of the environmental factors. They are widely adopted in various auto…