Localized content-based image retrieval using semi-supervised multiple instance learning

Dan Zhang; Zhenwei Shi; Yangqiu Song; Changshui Zhang

doi:10.1007/978-3-540-76386-4_16

Localized content-based image retrieval using semi-supervised multiple instance learning

Dan Zhang^*, Zhenwei Shi, Yangqiu Song, Changshui Zhang

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

7 Citations (Scopus)

Abstract

In this paper, we propose a Semi-Supervised Multiple-Instance Learning (SSMIL) algorithm, and apply it to Localized Content-Based Image Retrieval(LCBIR), where the goal is to rank all the images in the database, according to the object that users want to retrieve. SSMIL treats LCBIR as a Semi-Supervised Problem and utilize the unlabeled pictures to help improve the retrieval performance. The comparison result of SSMIL with several state-of-art algorithms is promising.

Original language	English
Title of host publication	Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings
Publisher	Springer Verlag
Pages	180-188
Number of pages	9
Edition	PART 1
ISBN (Print)	9783540763857
DOIs	https://doi.org/10.1007/978-3-540-76386-4_16
Publication status	Published - 2007
Externally published	Yes
Event	8th Asian Conference on Computer Vision, ACCV 2007 - Tokyo, Japan Duration: 18 Nov 2007 → 22 Nov 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4843 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th Asian Conference on Computer Vision, ACCV 2007
Country/Territory	Japan
City	Tokyo
Period	18/11/07 → 22/11/07

Access to Document

10.1007/978-3-540-76386-4_16

Cite this

Zhang, D., Shi, Z., Song, Y., & Zhang, C. (2007). Localized content-based image retrieval using semi-supervised multiple instance learning. In Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings (PART 1 ed., pp. 180-188). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4843 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-76386-4_16

Zhang, Dan ; Shi, Zhenwei ; Song, Yangqiu et al. / Localized content-based image retrieval using semi-supervised multiple instance learning. Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 180-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{2a23c301c93848589e526b5dbecf0943,

title = "Localized content-based image retrieval using semi-supervised multiple instance learning",

abstract = "In this paper, we propose a Semi-Supervised Multiple-Instance Learning (SSMIL) algorithm, and apply it to Localized Content-Based Image Retrieval(LCBIR), where the goal is to rank all the images in the database, according to the object that users want to retrieve. SSMIL treats LCBIR as a Semi-Supervised Problem and utilize the unlabeled pictures to help improve the retrieval performance. The comparison result of SSMIL with several state-of-art algorithms is promising.",

author = "Dan Zhang and Zhenwei Shi and Yangqiu Song and Changshui Zhang",

year = "2007",

doi = "10.1007/978-3-540-76386-4\_16",

language = "English",

isbn = "9783540763857",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 1",

pages = "180--188",

booktitle = "Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings",

edition = "PART 1",

note = "8th Asian Conference on Computer Vision, ACCV 2007 ; Conference date: 18-11-2007 Through 22-11-2007",

}

Zhang, D, Shi, Z, Song, Y & Zhang, C 2007, Localized content-based image retrieval using semi-supervised multiple instance learning. in Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4843 LNCS, Springer Verlag, pp. 180-188, 8th Asian Conference on Computer Vision, ACCV 2007, Tokyo, Japan, 18/11/07. https://doi.org/10.1007/978-3-540-76386-4_16

Localized content-based image retrieval using semi-supervised multiple instance learning. / Zhang, Dan; Shi, Zhenwei; Song, Yangqiu et al.
Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 180-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4843 LNCS, No. PART 1).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Localized content-based image retrieval using semi-supervised multiple instance learning

AU - Zhang, Dan

AU - Shi, Zhenwei

AU - Song, Yangqiu

AU - Zhang, Changshui

PY - 2007

Y1 - 2007

N2 - In this paper, we propose a Semi-Supervised Multiple-Instance Learning (SSMIL) algorithm, and apply it to Localized Content-Based Image Retrieval(LCBIR), where the goal is to rank all the images in the database, according to the object that users want to retrieve. SSMIL treats LCBIR as a Semi-Supervised Problem and utilize the unlabeled pictures to help improve the retrieval performance. The comparison result of SSMIL with several state-of-art algorithms is promising.

AB - In this paper, we propose a Semi-Supervised Multiple-Instance Learning (SSMIL) algorithm, and apply it to Localized Content-Based Image Retrieval(LCBIR), where the goal is to rank all the images in the database, according to the object that users want to retrieve. SSMIL treats LCBIR as a Semi-Supervised Problem and utilize the unlabeled pictures to help improve the retrieval performance. The comparison result of SSMIL with several state-of-art algorithms is promising.

UR - https://openalex.org/W65207188

UR - https://www.scopus.com/pages/publications/38149124900

U2 - 10.1007/978-3-540-76386-4_16

DO - 10.1007/978-3-540-76386-4_16

M3 - Conference Paper published in a book

SN - 9783540763857

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 180

EP - 188

BT - Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings

PB - Springer Verlag

T2 - 8th Asian Conference on Computer Vision, ACCV 2007

Y2 - 18 November 2007 through 22 November 2007

ER -

Zhang D, Shi Z, Song Y, Zhang C. Localized content-based image retrieval using semi-supervised multiple instance learning. In Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 180-188. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-76386-4_16

Localized content-based image retrieval using semi-supervised multiple instance learning

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