Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
Cocoa: Cross modality contrastive learning for sensor data
Self-Supervised Learning (SSL) is a new paradigm for learning discriminative
representations without labeled data, and has reached comparable or even state-of-the-art …
representations without labeled data, and has reached comparable or even state-of-the-art …
Beyond just vision: A review on self-supervised representation learning on multimodal and temporal data
Recently, Self-Supervised Representation Learning (SSRL) has attracted much attention in
the field of computer vision, speech, natural language processing (NLP), and recently, with …
the field of computer vision, speech, natural language processing (NLP), and recently, with …
Leveraging meta-learning to improve unsupervised domain adaptation
A Farhadi, A Sharifi - The Computer Journal, 2024 - academic.oup.com
Abstract Unsupervised Domain Adaptation (UDA) techniques in real-world scenarios often
encounter limitations due to their reliance on reducing distribution dissimilarity between …
encounter limitations due to their reliance on reducing distribution dissimilarity between …
Transfer learning in human activity recognition: A survey
SG Dhekane, T Ploetz - arXiv preprint arXiv:2401.10185, 2024 - arxiv.org
Sensor-based human activity recognition (HAR) has been an active research area, owing to
its applications in smart environments, assisted living, fitness, healthcare, etc. Recently …
its applications in smart environments, assisted living, fitness, healthcare, etc. Recently …
A perspective on human activity recognition from inertial motion data
Human activity recognition (HAR) using inertial motion data has gained a lot of momentum
in recent years both in research and industrial applications. From the abstract perspective …
in recent years both in research and industrial applications. From the abstract perspective …
COVID-19 variants and transfer learning for the emerging stringency indices
The pandemics in the history of world health organization have always left memorable
hallmarks, on the health care systems and on the economy of highly effected areas. The …
hallmarks, on the health care systems and on the economy of highly effected areas. The …
[HTML][HTML] Three-Dimensional Human Posture Recognition by Extremity Angle Estimation with Minimal IMU Sensor
Y Shiao, GY Chen, T Hoang - Sensors, 2024 - mdpi.com
Recently, posture recognition technology has advanced rapidly. Herein, we present a novel
posture angle calculation system utilizing a single inertial measurement unit and a spatial …
posture angle calculation system utilizing a single inertial measurement unit and a spatial …
Multi-task pre-training with soft biometrics for transfer-learning palmprint recognition
As a discriminative biometric modality, palmprint accommodates two attributes of soft
biometrics, namely chirality and gender. Our study reveals that the false matching of a pair of …
biometrics, namely chirality and gender. Our study reveals that the false matching of a pair of …