2 citations · 3 across the 3 of their papers we have counts for
5 papers
LightLLM: A Versatile Large Language Model for Predictive Light Sensing
Jiawei Hu, Hong Jia, Mahbub Hassan +3
We propose LightLLM, a model that fine tunes pre-trained large language models (LLMs) for light-based sensing tasks. It integrates a sensor data encoder to extract key features, a…
Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health
Yongquan Hu, Shuning Zhang, Ting Dang +4
Integrating physiological signals such as electroencephalogram (EEG), with other data such as interview audio, may offer valuable multimodal insights into psychological states or n…
LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms
Young D. Kwon, Jagmohan Chauhan, Hong Jia +2
Continual Learning (CL) allows applications such as user personalization and household robots to learn on the fly and adapt to context. This is an important feature when context, a…
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction
Yu Wu, Dimitris Spathis, Hong Jia +5
Deep learning models have shown great promise in various healthcare monitoring applications. However, most healthcare datasets with high-quality (gold-standard) labels are small-sc…
Spectral-Loc: Indoor Localization using Light Spectral Information
Yanxiang Wang, Jiawei Hu, Hong Jia +5
For indoor settings, we investigate the impact of location on the spectral distribution of the received light, i.e., the intensity of light for different wavelengths. Our investiga…