Deep Activity Recognition Models with Triaxial Accelerometers

• Main Authors: Abu Alsheikh, Mohammad, Selim, Ahmed, Niyato, Dusit, Doyle, Linda, Lin, Shaowei, Tan, Hwee-Pink
• 其他作者: School of Computer Science and Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2017
• 主題: Learning; Human-Computer Interaction
• 在線閱讀: https://hdl.handle.net/10356/80702; http://hdl.handle.net/10220/42197; https://arxiv.org/abs/1511.04664
• 機構: Nanyang Technological University

Despite the widespread installation of accelerometers in almost all mobile phones and wearable devices, activity recognition using accelerometers is still immature due to the poor recognition accuracy of existing recognition methods and the scarcity of labeled training data. We consider the problem...