Mobile based big data design patent image retrieval system via Lp norm deep learning approach

Jing Su; Bingo W. K. Ling; Qingyun Dai; Jun Xiao; Kim-Fung Tsang

doi:10.1109/IECON.2015.7392866

Mobile based big data design patent image retrieval system via Lp norm deep learning approach

Jing Su
, Bingo W. K. Ling^*
, Qingyun Dai
, Jun Xiao
, Kim-Fung Tsang

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

This paper proposes a mobile based big data design patent image retrieval system via a deep learning approach. The images are represented via sparse vectors by a dictionary. The joint representation and dictionary design problem is formulated as a mixed L2 and Lp optimization problem. An iterative algorithm is employed for finding a locally optimal solution. Experimental results show that the retrieval accuracy is high.

Original language	English
Title of host publication	IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Pages	4886-4889
ISBN (Print)	9781479917624
DOIs	https://doi.org/10.1109/IECON.2015.7392866
Publication status	Published - Nov 2015
Event	41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015 - Yokohama, Japan Duration: 9 Nov 2015 → 12 Nov 2015

Conference

Conference	41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015
Place	Japan
City	Yokohama
Period	9/11/15 → 12/11/15

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10.1109/IECON.2015.7392866

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@inproceedings{1cbb835692ad4ba1b5f486ae65662e53,

title = "Mobile based big data design patent image retrieval system via Lp norm deep learning approach",

abstract = "This paper proposes a mobile based big data design patent image retrieval system via a deep learning approach. The images are represented via sparse vectors by a dictionary. The joint representation and dictionary design problem is formulated as a mixed L2 and Lp optimization problem. An iterative algorithm is employed for finding a locally optimal solution. Experimental results show that the retrieval accuracy is high.",

author = "Jing Su and Ling, \{Bingo W. K.\} and Qingyun Dai and Jun Xiao and Kim-Fung Tsang",

year = "2015",

month = nov,

doi = "10.1109/IECON.2015.7392866",

language = "English",

isbn = "9781479917624",

pages = "4886--4889",

booktitle = "IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

address = "United States",

note = "41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015 ; Conference date: 09-11-2015 Through 12-11-2015",

}

Su, J, Ling, BWK, Dai, Q, Xiao, J & Tsang, K-F 2015, Mobile based big data design patent image retrieval system via Lp norm deep learning approach. in IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society., 7392866, IEEE, pp. 4886-4889, 41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015, Yokohama, Japan, 9/11/15. https://doi.org/10.1109/IECON.2015.7392866

Mobile based big data design patent image retrieval system via Lp norm deep learning approach. / Su, Jing; Ling, Bingo W. K.; Dai, Qingyun et al.
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2015. p. 4886-4889 7392866.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Mobile based big data design patent image retrieval system via Lp norm deep learning approach

AU - Su, Jing

AU - Ling, Bingo W. K.

AU - Dai, Qingyun

AU - Xiao, Jun

AU - Tsang, Kim-Fung

PY - 2015/11

Y1 - 2015/11

N2 - This paper proposes a mobile based big data design patent image retrieval system via a deep learning approach. The images are represented via sparse vectors by a dictionary. The joint representation and dictionary design problem is formulated as a mixed L2 and Lp optimization problem. An iterative algorithm is employed for finding a locally optimal solution. Experimental results show that the retrieval accuracy is high.

AB - This paper proposes a mobile based big data design patent image retrieval system via a deep learning approach. The images are represented via sparse vectors by a dictionary. The joint representation and dictionary design problem is formulated as a mixed L2 and Lp optimization problem. An iterative algorithm is employed for finding a locally optimal solution. Experimental results show that the retrieval accuracy is high.

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DO - 10.1109/IECON.2015.7392866

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781479917624

SP - 4886

EP - 4889

BT - IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society

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T2 - 41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015

Y2 - 9 November 2015 through 12 November 2015

ER -

Mobile based big data design patent image retrieval system via Lp norm deep learning approach

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