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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Veröffentlicht in:	IEEE transactions on computer-aided design of integrated circuits and systems Jg. 38; H. 11; S. 2127 - 2138
Hauptverfasser:	Safaei, Amin, Wu, Q. M. Jonathan, Akilan, Thangarajah, Yang, Yimin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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
Online-Zugang:	Volltext
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