2 citations · 3 across the 2 of their papers we have counts for
5 papers
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
Kaixuan Chen, Dalin Zhang, Lina Yao +3
The vast proliferation of sensor devices and Internet of Things enables the applications of sensor-based activity recognition. However, there exist substantial challenges that coul…
Multi-agent Attentional Activity Recognition
Kaixuan Chen, Lina Yao, Dalin Zhang +2
Multi-modality is an important feature of sensor based activity recognition. In this work, we consider two inherent characteristics of human activities, the spatially-temporally va…
Metabolize Neural Network
Dan Dai, Zhiwen Yu, Yang Hu +2
The metabolism of cells is the most basic and important part of human function. Neural networks in deep learning stem from neuronal activity. It is self-evident that the significan…
Competitive Inner-Imaging Squeeze and Excitation for Residual Network
Yang Hu, Guihua Wen, Mingnan Luo +3
Residual networks, which use a residual unit to supplement the identity mappings, enable very deep convolutional architecture to operate well, however, the residual architecture ha…
Fullie and Wiselie: A Dual-Stream Recurrent Convolutional Attention Model for Activity Recognition
Kaixuan Chen, Lina Yao, Tao Gu +3
Multimodal features play a key role in wearable sensor based Human Activity Recognition (HAR). Selecting the most salient features adaptively is a promising way to maximize the eff…