Mohamed Ragab

According to our database, Mohamed Ragab authored at least 27 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Contrastive Domain Adaptation for Time-Series Via Temporal Mixup.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

IEEE Trans. Artif. Intell., March, 2024

Self-Supervised Autoregressive Domain Adaptation for Time Series Data.

Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li

IEEE Trans. Neural Networks Learn. Syst., January, 2024

Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias.

Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo

CoRR, 2024

2023

Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Diverse and consistent multi-view networks for semi-supervised regression.

Cuong Manh Nguyen, Arun Raja, Le Zhang, Xun Xu, Balagopal Unnikrishnan, Mohamed Ragab, Kangkang Lu, Chuan-Sheng Foo

Mach. Learn., July, 2023

ADAST: Attentive Cross-Domain EEG-Based Sleep Staging Framework With Iterative Self-Training.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan

IEEE Trans. Emerg. Top. Comput. Intell., February, 2023

ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data.

Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

ACM Trans. Knowl. Discov. Data, 2023

Label-efficient Time Series Representation Learning: A Review.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

CoRR, 2023

Source-Free Domain Adaptation with Temporal Imputation for Time Series Data.

Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

AA-DL: AoI-Aware Deep Learning Approach for D2D-Assisted Industrial IoT.

Hossam M. Farag, Mohamed Ragab, Cedomir Stefanovic

Proceedings of the IEEE Global Conference on Artificial Intelligence and Internet of Things, 2023

2022

Towards practical data-driven predictive maintenance: a robust and generalizable deep learning approach

Mohamed Ragab

PhD thesis, 2022

Conditional Contrastive Domain Generalization for Fault Diagnosis.

Mohamed Ragab, Zhenghua Chen, Wenyu Zhang, Emadeldeen Eldele, Min Wu, Chee Keong Kwoh, Xiaoli Li

IEEE Trans. Instrum. Meas., 2022

Contrastive adversarial knowledge distillation for deep model compression in time-series regression tasks.

Qing Xu, Zhenghua Chen, Mohamed Ragab, Chao Wang, Min Wu, Xiaoli Li

Neurocomputing, 2022

CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

CoRR, 2022

Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

CoRR, 2022

Beat-Based PPG-ABP Cleaning Technique for Blood Pressure Estimation.

Mostafa Salah, Osama A. Omer, Loay Hassan, Mohamed Ragab, Ammar Mostafa Hassan, Ahmed Abdelreheem

IEEE Access, 2022

Domain Generalization via Selective Consistency Regularization for Time Series Classification.

Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo

Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021

Adversarial Multiple-Target Domain Adaptation for Fault Classification.

Mohamed Ragab, Zhenghua Chen, Min Wu, Haoliang Li, Chee-Keong Kwoh, Ruqiang Yan, Xiaoli Li

IEEE Trans. Instrum. Meas., 2021

Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction.

Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li

IEEE Trans. Ind. Informatics, 2021

Attention-based sequence to sequence model for machine remaining useful life prediction.

Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li

Neurocomputing, 2021

Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan

CoRR, 2021

Time-Series Representation Learning via Temporal and Contextual Contrasting.

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Robust Domain-Free Domain Generalization with Class-Aware Alignment.

Wenyu Zhang, Mohamed Ragab, Ramón Sagarna

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Compressive sensing MRI reconstruction using empirical wavelet transform and grey wolf optimizer.

Mohamed Ragab, Osama Ahmed Omer, Mohamed Abdel-Nasser

Neural Comput. Appl., 2020

Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction.

Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Ruqiang Yan, Xiaoli Li

CoRR, 2020

Secure Transfer Learning for Machine Fault Diagnosis Under Different Operating Conditions.

Chao Jin, Mohamed Ragab, Khin Mi Mi Aung

Proceedings of the Provable and Practical Security - 14th International Conference, ProvSec 2020, Singapore, November 29, 2020

Adversarial Transfer Learning for Machine Remaining Useful Life Prediction.

Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

Proceedings of the IEEE International Conference on Prognostics and Health Management, 2020