Mobile computing has also adopted these powerful modeling approaches, delivering astonishing success in the field's core application domains, including the ongoing transformation of human activity recognition technology through machine learning.关键词: ieee computer society ...
Human activity recognition (HAR) based on sensor data is a significant problem in pervasive computing. In recent years, deep learning has become the dominating approach in this field, due to its high accuracy. However, it is difficult to make accurate identification for the activities of one ind...
人类行为识别(Human activity recognition,也可以翻译成人体动作识别,看具体的语境和研究任务)在人们的日常生活中起着重要的作用。然而,获取准确的带标签的数据是昂贵和耗时的。为了解决这一问题,迁移学习利用源域的已标记样本来标注目标域,而目标域的标签很少或没有标签。不幸的是,当有多个源域(怎样算是有多个源域...
Human activity recognition using wearable sensors: a deep learning approach HUMAN ACTIVITY RECOGNITION USING WEARABLE SENSORS: A DEEP LEARNING APPROACH J Xue 被引量: 0发表: 2020年 A Deep Learning Framework for Human Activity Recognition Using Smartphone Data HUMAN ACTIVITY RECOGNITION USING WEARABLE SENS...
Attention-based deep learning framework for human activity recognition with user adaptation IEEE Sens J (2021) IncelO.Durmaz. et al. On-device deep learning for mobile and wearable sensing applications: A review IEEE Sens J (2023) VavoulasG. et al. The MobiAct dataset: Recognition of act...
Transition-aware human activity recognition using an ensemble deep learning framework A robust framework is proposed for detecting static and dynamic human activities, including Postural Transitions.The proposed framework is used for sensor-... SI Khan,H Dawood,MA Khan,... - 《Computers in Human Be...
Our focus in this research is on the use of deep learning approaches for human activity recognition (HAR) scenario, in which inputs are multichannel time series signals acquired from a set of body-worn inertial sensors and outputs are predefined human activities. Here, we present a feature lear...
Human Action Recognition (HAR) is a popular area of research in computer vision due to its wide range of applications such as surveillance, health care, and gaming, etc. Action recognition based on 3D skeleton data allows simplistic, cost-efficient model
Learning Deep and Shallow Features for Human Activity RecognitionAn important application domain for Machine learning is sentiment classification. Here, the traditional approach is to represent documents using a Bag-Of-Words (BOW) model, where individual terms are used as features. However, the BOW ...
Human activity recognition (HAR) is currently recognized as a key element of a more general framework designed to perform continuous monitoring of human behaviors in the area of ambient assisted living (AAL), well-being management, medical diagnosis, elderly care, rehabilitation, entertainment, and ...