arXiv:2607. 11839v1 Announce Type: cross Abstract: This paper presents a cascaded Low-Rank Adaptation (LoRA)-based multimodal fusion framework for action and activity recognition in healthcare-oriented training environments.
By Divya Mereddy, Jeevan Beedareddy
arXiv:2606. 27886v1 Announce Type: new Abstract: Recent advances in Human Activity Recognition (HAR) from wearable sensors have shown that multi-modal deep learning models consistently outperform their uni-modal counterparts.
By Ahmed Mohamady, Robin Burchard, Kristof Van Laerhoven
Multimodal fusion learning (MFL) has shown great potential in the medical domain, where we are faced with disparate data modalities such as imaging, clinical records, and omics. However, existing MFL strategies face several major challenges.
arXiv:2609.36848v1 Announce Type: new
Abstract: Human Activity Recognition (HAR) through wearable sensors greatly improves the quality of human life through its multiple applications. For HAR, multi-...
By Nafees Ahmad, Ho-fung Leung, Muhammad Adil Abid, Sadia Shakil
arXiv:2609.08038v2 Announce Type: cross
Abstract: Smart healthcare monitoring systems require precise action recognition to ensure well-being and timely intervention in critical situations such as fa...
By Diwas Lamsal, Pramod Wickramatilake, Jednipat Moonrinta, Mongkol Ekpanyapong, Matthew N. Dailey
arXiv:2608. 06122v1 Announce Type: cross Abstract: Inspired by recent evidence that transformer architectures benefit from Self-PreTraining (SPT) on long-context benchmarks, we investigate whether similar gains extend to multimodal, multivariate, and even simple univariate medical time series.
By Omar Coser, Antonio Orvieto, Paolo Soda, Loredana Zollo