FreqMAE: Frequency-Aware Masked Autoencoder for Multi-Modal IoT Sensing

D Kara, T Kimura, S Liu, J Li, D Liu, T Wang… - Proceedings of the …, 2024 - dl.acm.org
This paper presents FreqMAE, a novel self-supervised learning framework that synergizes
masked autoencoding (MAE) with physics-informed insights to capture feature patterns in …

IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition

Z Hu, A Radmehr, Y Zhang, S Pan… - Proceedings of the ACM on …, 2024 - dl.acm.org
While occlusal diseases-the main cause of tooth loss--significantly impact patients' teeth and
well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing …

Artificial Intelligence of Things: A Survey

SI Siam, H Ahn, L Liu, S Alam, H Shen, Z Cao… - ACM Transactions on …, 2024 - dl.acm.org
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …

PhyMask: An Adaptive Masking Paradigm for Efficient Self-Supervised Learning in IoT

D Kara, T Kimura, Y Chen, J Li, R Wang… - Proceedings of the …, 2024 - dl.acm.org
This paper introduces PhyMask, an adaptive masking paradigm designed to enhance the
efficiency and interpretability of Masked Autoencoders (MAEs) in analyzing IoT sensing …

Poster: PrivaSee: Augmented Reality-Enabled Privacy Perception Visualization for Internet of Things

Y Zhang, S Du, J Wen, R Likamwa, S Fang… - Proceedings of the 22nd …, 2024 - dl.acm.org
Internet of Things (IoT) provides a wide range of services to improve convenience and
comfort in our daily lives. However, various sensors equipped on IoT devices often raise …