Distilling the knowledge from handcrafted features for human activity recognition

• المؤلفون الرئيسيون: Chen, Zhenghua, Zhang, Le, Cao, Zhiguang, Guo, Jing
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2019
• الموضوعات: DRNTU::Engineering::Electrical and electronic engineering; Human Activity Recognition; Deep Long Short-term Memory (LSTM) Network
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/86019; http://hdl.handle.net/10220/48267

Human activity recognition is a core problem in intelligent automation systems due to its far-reaching applications including ubiquitous computing, health-care services, and smart living. Due to the nonintrusive property of smartphones, smartphone sensors are widely used for the identification of hu...