A New Framework and Implementation Technology of Deep Collaborative Front-End Computing

Linna Wang; Yitong Xia; Cheng Wang; Baochang Zhang

doi:10.1109/ICIEA48937.2020.9248122

A New Framework and Implementation Technology of Deep Collaborative Front-End Computing

Linna Wang
, Yitong Xia
, Cheng Wang
, Baochang Zhang

School of Artificial Intelligence(Institute of Artificial Intelligence)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In order to further enhance the perception ability of mobile devices and promote their development towards intellectualization and autonomy. On the basis of the existing related research, aiming at the typical problems existing in the current research, the lightweight machine learning framework for collaborative computing is carried out. This framework can implement object detection methods such as Haar and Adaboost, HOG and SVM. It mainly discusses the practicability of manually designed features for mobile platforms. In order to further improve the system performance, the research on efficient computer vision technologies such as object detection and tracking related theories and technologies is carried out with embedded equipment with the artificial intelligence chip as the core processor.

Original language	English
Title of host publication	Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1843-1847
Number of pages	5
ISBN (Electronic)	9781728151694
DOIs	https://doi.org/10.1109/ICIEA48937.2020.9248122
State	Published - 9 Nov 2020
Event	15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020 - Virtual, Kristiansand, Norway Duration: 9 Nov 2020 → 13 Nov 2020

Publication series

Name	Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020

Conference

Conference	15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020
Country/Territory	Norway
City	Virtual, Kristiansand
Period	9/11/20 → 13/11/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

algorithm transplantation
collaborative theory
object detection

Access to Document

10.1109/ICIEA48937.2020.9248122

Cite this

Wang, L., Xia, Y., Wang, C., & Zhang, B. (2020). A New Framework and Implementation Technology of Deep Collaborative Front-End Computing. In Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020 (pp. 1843-1847). Article 9248122 (Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA48937.2020.9248122

Wang, Linna ; Xia, Yitong ; Wang, Cheng et al. / A New Framework and Implementation Technology of Deep Collaborative Front-End Computing. Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 1843-1847 (Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020).

@inproceedings{0f7753c3ae3e4d009feb861ae051c476,

title = "A New Framework and Implementation Technology of Deep Collaborative Front-End Computing",

abstract = "In order to further enhance the perception ability of mobile devices and promote their development towards intellectualization and autonomy. On the basis of the existing related research, aiming at the typical problems existing in the current research, the lightweight machine learning framework for collaborative computing is carried out. This framework can implement object detection methods such as Haar and Adaboost, HOG and SVM. It mainly discusses the practicability of manually designed features for mobile platforms. In order to further improve the system performance, the research on efficient computer vision technologies such as object detection and tracking related theories and technologies is carried out with embedded equipment with the artificial intelligence chip as the core processor.",

keywords = "algorithm transplantation, collaborative theory, object detection",

author = "Linna Wang and Yitong Xia and Cheng Wang and Baochang Zhang",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020 ; Conference date: 09-11-2020 Through 13-11-2020",

year = "2020",

month = nov,

day = "9",

doi = "10.1109/ICIEA48937.2020.9248122",

language = "英语",

series = "Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1843--1847",

booktitle = "Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020",

address = "美国",

}

Wang, L, Xia, Y, Wang, C & Zhang, B 2020, A New Framework and Implementation Technology of Deep Collaborative Front-End Computing. in Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020., 9248122, Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020, Institute of Electrical and Electronics Engineers Inc., pp. 1843-1847, 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020, Virtual, Kristiansand, Norway, 9/11/20. https://doi.org/10.1109/ICIEA48937.2020.9248122

A New Framework and Implementation Technology of Deep Collaborative Front-End Computing. / Wang, Linna; Xia, Yitong; Wang, Cheng et al.
Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1843-1847 9248122 (Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A New Framework and Implementation Technology of Deep Collaborative Front-End Computing

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AU - Xia, Yitong

AU - Wang, Cheng

AU - Zhang, Baochang

PY - 2020/11/9

Y1 - 2020/11/9

N2 - In order to further enhance the perception ability of mobile devices and promote their development towards intellectualization and autonomy. On the basis of the existing related research, aiming at the typical problems existing in the current research, the lightweight machine learning framework for collaborative computing is carried out. This framework can implement object detection methods such as Haar and Adaboost, HOG and SVM. It mainly discusses the practicability of manually designed features for mobile platforms. In order to further improve the system performance, the research on efficient computer vision technologies such as object detection and tracking related theories and technologies is carried out with embedded equipment with the artificial intelligence chip as the core processor.

AB - In order to further enhance the perception ability of mobile devices and promote their development towards intellectualization and autonomy. On the basis of the existing related research, aiming at the typical problems existing in the current research, the lightweight machine learning framework for collaborative computing is carried out. This framework can implement object detection methods such as Haar and Adaboost, HOG and SVM. It mainly discusses the practicability of manually designed features for mobile platforms. In order to further improve the system performance, the research on efficient computer vision technologies such as object detection and tracking related theories and technologies is carried out with embedded equipment with the artificial intelligence chip as the core processor.

KW - algorithm transplantation

KW - collaborative theory

KW - object detection

UR - https://www.scopus.com/pages/publications/85097565730

U2 - 10.1109/ICIEA48937.2020.9248122

DO - 10.1109/ICIEA48937.2020.9248122

M3 - 会议稿件

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T3 - Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020

SP - 1843

EP - 1847

BT - Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020

Y2 - 9 November 2020 through 13 November 2020

ER -

Wang L, Xia Y, Wang C, Zhang B. A New Framework and Implementation Technology of Deep Collaborative Front-End Computing. In Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 1843-1847. 9248122. (Proceedings of the 15th IEEE Conference on Industrial Electronics and Applications, ICIEA 2020). doi: 10.1109/ICIEA48937.2020.9248122

A New Framework and Implementation Technology of Deep Collaborative Front-End Computing

Abstract

Publication series

Conference

UN SDGs

Keywords

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