Changing Mobile Data Analysis through Deep Learning

被引：7
|
作者：
Kasnesis, Panagiotis [1 ]
Patrikakis, Charalampos Z. [3 ]
Venieris, Iakovos S. [2 ]
机构：
[1] Natl Tech Univ Athens, Dept Elect & Comp Engn, Athens, Greece
[2] Natl Tech Univ Athens, Sch Elect & Comp Engn, Athens, Greece
[3] Piraeus Univ Appl Sci, Dept Elect Engn, Aigaleo, Greece
来源：
IT PROFESSIONAL | 2017年 / 19卷 / 03期
关键词：
accelerometer data; big data; context-awareness; data analytics; deep learning; human activity recognition; mobile data analysis;
D O I：
10.1109/MITP.2017.52
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The authors present common mobile context-aware applications and reference current mobile data analysis practices and approaches. They propose using deep learning to analyze sensor data from mobile devices and discuss open issues related to this approach.
引用
收藏
页码：17 / 23
页数：7
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