System-on-a-Chip (SoC)-Based Hardware Acceleration for an Online Sequential Extreme Learning Machine (OS-ELM)

Machine learning algorithms such as those for object classification in images, video content analysis, and human action recognition are used to extract meaningful information from data recorded by image sensors and cameras. Among the existing machine learning algorithms for such purposes, extreme le...

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Vydané v:	IEEE transactions on computer-aided design of integrated circuits and systems Ročník 38; číslo 11; s. 2127 - 2138
Hlavní autori:	Safaei, Amin, Wu, Q. M. Jonathan, Akilan, Thangarajah, Yang, Yimin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Acceleration Algorithms Artificial intelligence Artificial neural networks Computer architecture Content analysis Embedded systems Extreme learning machine (ELM) Field programmable gate arrays Hardware hardware (HW) Human activity recognition Human motion Image classification Machine learning Machine learning algorithms Matrix decomposition neural networks (NNs) online sequential ELM (OS-ELM) Pipelining (computers) Power consumption System on chip system-on-a-chip field-programmable gate array (SoC FPGA) Training Video data
ISSN:	0278-0070, 1937-4151
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