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HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™

Video is playing the vital role in Internet of Things (IoT) industry, as it is able to provide multi-dimensional data and handling complex task compared to typical sensor. Through image processing and video analytic, many industries such as factories, cities and offices will have improved in terms o...

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Main Author: YEW SHUN, OOI
Format: Final Year Project
Language:English
Published: 2018
Online Access:http://utpedia.utp.edu.my/19199/1/Final%20Dissertation_19812.pdf
http://utpedia.utp.edu.my/19199/
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record_format eprints
spelling my-utp-utpedia.191992019-06-20T08:44:46Z http://utpedia.utp.edu.my/19199/ HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™ YEW SHUN, OOI Video is playing the vital role in Internet of Things (IoT) industry, as it is able to provide multi-dimensional data and handling complex task compared to typical sensor. Through image processing and video analytic, many industries such as factories, cities and offices will have improved in terms of the output’s efficiency and productivity. This technology can be further improved through implementing artificial intelligence, to yield faster and more accurate output. However, one of the biggest challenge of adapting video in various field is the hardware limitation. A typical video enabled IoT system usually require high performance specification, and with the addition of artificial intelligence algorithm, the requirement for the hardware performance is even higher. Intel had come out with a new product, Movidius Vision Processing Unit, which is able to run the video processing and machine learning with low power consumption while providing a high processing capability. This paper proposes a new add in card design powered with the VPU system on chip which is more suitable to adopt by other existing system, to improve the performance and reduce the system’s processor workload. 2018-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/19199/1/Final%20Dissertation_19812.pdf YEW SHUN, OOI (2018) HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™. UNSPECIFIED.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
description Video is playing the vital role in Internet of Things (IoT) industry, as it is able to provide multi-dimensional data and handling complex task compared to typical sensor. Through image processing and video analytic, many industries such as factories, cities and offices will have improved in terms of the output’s efficiency and productivity. This technology can be further improved through implementing artificial intelligence, to yield faster and more accurate output. However, one of the biggest challenge of adapting video in various field is the hardware limitation. A typical video enabled IoT system usually require high performance specification, and with the addition of artificial intelligence algorithm, the requirement for the hardware performance is even higher. Intel had come out with a new product, Movidius Vision Processing Unit, which is able to run the video processing and machine learning with low power consumption while providing a high processing capability. This paper proposes a new add in card design powered with the VPU system on chip which is more suitable to adopt by other existing system, to improve the performance and reduce the system’s processor workload.
format Final Year Project
author YEW SHUN, OOI
spellingShingle YEW SHUN, OOI
HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
author_facet YEW SHUN, OOI
author_sort YEW SHUN, OOI
title HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
title_short HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
title_full HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
title_fullStr HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
title_full_unstemmed HIGH DENSITY DEEP LEARNING-LITE WITH INTEL OPENVINO™
title_sort high density deep learning-lite with intel openvino™
publishDate 2018
url http://utpedia.utp.edu.my/19199/1/Final%20Dissertation_19812.pdf
http://utpedia.utp.edu.my/19199/
_version_ 1739832601156255744
score 13.160551

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