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Machine Learning in Resource-Scarce Embedded Systems, FPGAs, and End-Devices: A Survey
2019
Electronics
The number of devices connected to the Internet is increasing, exchanging large amounts of data, and turning the Internet into the 21st-century silk road for data. This road has taken machine learning to new areas of applications. However, machine learning models are not yet seen as complex systems that must run in powerful computers (i.e., Cloud). As technology, techniques, and algorithms advance, these models are implemented into more computational constrained devices. The following paper
doi:10.3390/electronics8111289
fatcat:uy45m4jnhfeypk5cmr5jmm3emq