The Deep (Learning) Transformation of Mobile and Embedded Computing
Computer2018Vol. 51(5), pp. 12–16
Citations Over TimeTop 10% of 2018 papers
Abstract
Mobile and embedded devices increasingly rely on deep neural networks to understand the world—a feat that would have overwhelmed their system resources only a few years ago. Further integration of machine learning and embedded/mobile systems will require additional breakthroughs of efficient learning algorithms that can function under fluctuating resource constraints, giving rise to a field that straddles computer architecture, software systems, and artificial intelligence.
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