A systematic review of human activity recognition based on mobile devices: overview, progress and trends

Y Yin, L **e, Z Jiang, F **ao, J Cao… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Due to the ever-growing powers in sensing, computing, communicating and storing, mobile
devices (eg, smartphone, smartwatch, smart glasses) become ubiquitous and an …

Distributional and spatial-temporal robust representation learning for transportation activity recognition

J Liu, Y Liu, W Zhu, X Zhu, L Song - Pattern Recognition, 2023 - Elsevier
Transportation activity recognition (TAR) provides valuable support for intelligent
transportation applications, such as urban transportation planning, driving behavior …

Resource aware clustering for tackling the heterogeneity of participants in federated learning

R Mishra, HP Gupta, G Banga… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated Learning is a training framework that enables multiple participants to
collaboratively train a shared model while preserving data privacy. The heterogeneity of …

Robust and ubiquitous mobility mode estimation using limited cellular information

S Mostafa, KA Harras, M Youssef - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Recent mobility mode estimation systems propose using signals from the serving cell tower
only to be deployable on all phones. However, all available solutions depend on statistical …

APPN: An Attention-based Pseudo-label Propagation Network for few-shot learning with noisy labels

J Chen, S Deng, D Teng, D Chen, T Jia, H Wang - Neurocomputing, 2024 - Elsevier
Few-shot learning has garnered significant attention in deep learning as an effective
approach for addressing the issue of data scarcity. Conventionally, training datasets in few …

Long-short-view aware multi-agent reinforcement learning for signal snippet distillation in delirium movement detection

Q Pan, H Wang, J Lou, Y Zhang, B Ji, S Li - Information Sciences, 2024 - Elsevier
Automatic movement analysis utilizing surveillance video is believed to be an important and
convenient way for timely delirium detection in an Intensive Care Unit (ICU). However, video …

ModeSense: Ubiquitous and accurate transportation mode detection using serving cell tower information

S Mostafa, M Youssef, KA Harras - Proceedings of the 32nd ACM …, 2024 - dl.acm.org
Recent transportation mode detection systems propose leveraging signals from only the
serving cell tower to ensure ubiquity and practical deployability across all phones. However …

Utilizing transfer learning and pre-trained models for effective forest fire detection: A case study of uttarakhand

HP Gupta, R Mishra - arxiv preprint arxiv:2410.06743, 2024 - arxiv.org
Forest fires pose a significant threat to the environment, human life, and property. Early
detection and response are crucial to mitigating the impact of these disasters. However …

Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies

X Wang, W Jia - arxiv preprint arxiv:2501.03265, 2025 - arxiv.org
The emergence of 5G and edge computing hardware has brought about a significant shift in
artificial intelligence, with edge AI becoming a crucial technology for enabling intelligent …

Noise-resilient federated learning: Suppressing noisy labels in the local datasets of participants

R Mishra, HP Gupta, T Dutta - IEEE INFOCOM 2022-IEEE …, 2022 - ieeexplore.ieee.org
Federated Learning (FL) is a novel paradigm of collaboratively training a model using local
datasets of multiple participants. FL maintains data privacy and keeps local datasets …