Activity recognition plays a critical role in various applications, such as medical monitoring
and rehabilitation. Deep learning has recently made great development in the wearable …

Due to rapid development of sensor technology, human activity recognition (HAR) using
wearable inertial sensors has recently become a new research hotspot. Deep learning …

Deep convolutional neural networks (CNNs) achieve state-of-the-art performance in
wearable human activity recognition (HAR), which has become a new research trend in …

Recently, convolutional neural networks (CNNs) have set latest state-of-the-art on various
human activity recognition (HAR) datasets. However, deep CNNs often require more …

Recently, deep learning has represented an important research trend in human activity
recognition (HAR). In particular, deep convolutional neural networks (CNNs) have achieved …

Convolutional neural networks (CNNs) have shown great promise in human activity
recognition (HAR), but long-term dependencies in time series data can be difficult to capture …

Recently, deep learning, which are able to extract automatically features from data, has
achieved state-of-the-art performance across a variety of sensor based human activity …

Recent years have witnessed significant success of convolutional neural networks (CNNs)
in human activity recognition (HAR) using wearable sensors. Nevertheless, prior works have …

Human activity recognition (HAR) based on sensor networks is an important research
direction in the fields of pervasive computing and body area network. Existing researches …

During the past decade, human activity recognition (HAR) using wearable sensors has
become a new research hot spot due to its extensive use in various application domains …