Deep Activity Recognition Models with Triaxial Accelerometers

• المؤلفون الرئيسيون: Abu Alsheikh, Mohammad, Selim, Ahmed, Niyato, Dusit, Doyle, Linda, Lin, Shaowei, Tan, Hwee-Pink
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2017
• الموضوعات: Learning; Human-Computer Interaction
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/80702; http://hdl.handle.net/10220/42197; https://arxiv.org/abs/1511.04664

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...