Deep Learning on Mobile and Embedded Devices: State-of-the-art, Challenges, and Future Directions.
Yanjiao ChenBaolin ZhengZihan ZhangQian WangChao ShenQian ZhangPublished in: ACM Comput. Surv. (2020)
Keyphrases
- future directions
- deep learning
- embedded devices
- lessons learned
- mobile devices
- current challenges
- mobile commerce
- unsupervised learning
- embedded systems
- mobile phone
- machine learning
- advanced technologies
- mobile learning
- unsupervised feature learning
- weakly supervised
- mobile applications
- mobile users
- limited memory
- context aware
- learning activities
- case study
- data storage
- flash memory
- mental models
- communication technologies
- probabilistic model
- wireless sensor networks
- real world
- real time