Adaboost for concrete type of keywords annotation

Wei Chao Lin; Yan Ze Chen; Shu Yuan Chen

Adaboost for concrete type of keywords annotation

Wei Chao Lin^*, Yan Ze Chen, Shu Yuan Chen

^*Corresponding author for this work

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

Abstract

The semantic gap presents an arduous task in semantic-based image retrieval investigations. In this paper, the author proposes the AdaBoost learning algorithm for large vocabulary classification. The main finding of this investigation is that using Gentle AdaBoost for image classification produced excellent results in terms of precision and the F-measure. With 190 concrete keywords categorisation, AdaBoost renders more keywords assignable and allows a significant improvement in all accuracy measures: precision, recall and F-measure. An AdaBoost vs. SVMs comparison showed that AdaBoost was an effective classifier using the one-versus-the-rest mode of operation.

Original language	English
Title of host publication	Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018
Editors	Craig Douglas, Korsunsky Korsunsky, Oscar Castillo, S. I. Ao, David Dagan Feng
Publisher	Newswood Limited
Pages	293-298
Number of pages	6
ISBN (Electronic)	9789881404787
State	Published - 2018
Externally published	Yes
Event	2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018 - Hong Kong, Hong Kong Duration: 14 03 2018 → 16 03 2018

Publication series

Name	Lecture Notes in Engineering and Computer Science
Volume	2233
ISSN (Print)	2078-0958

Conference

Conference	2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018
Country/Territory	Hong Kong
City	Hong Kong
Period	14/03/18 → 16/03/18

Bibliographical note

Publisher Copyright:
© 2018 Newswood Limited. All rights reserved.

Keywords

Image annotation 、 Content-based image retrieval、AdaBoost learning algorithm

Cite this

Lin, W. C., Chen, Y. Z., & Chen, S. Y. (2018). Adaboost for concrete type of keywords annotation. In C. Douglas, K. Korsunsky, O. Castillo, S. I. Ao, & D. D. Feng (Eds.), Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018 (pp. 293-298). (Lecture Notes in Engineering and Computer Science; Vol. 2233). Newswood Limited.

Lin, Wei Chao ; Chen, Yan Ze ; Chen, Shu Yuan. / Adaboost for concrete type of keywords annotation. Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018. editor / Craig Douglas ; Korsunsky Korsunsky ; Oscar Castillo ; S. I. Ao ; David Dagan Feng. Newswood Limited, 2018. pp. 293-298 (Lecture Notes in Engineering and Computer Science).

@inproceedings{7d6730d1d1764d07a3e7e0b75bc18481,

title = "Adaboost for concrete type of keywords annotation",

abstract = "The semantic gap presents an arduous task in semantic-based image retrieval investigations. In this paper, the author proposes the AdaBoost learning algorithm for large vocabulary classification. The main finding of this investigation is that using Gentle AdaBoost for image classification produced excellent results in terms of precision and the F-measure. With 190 concrete keywords categorisation, AdaBoost renders more keywords assignable and allows a significant improvement in all accuracy measures: precision, recall and F-measure. An AdaBoost vs. SVMs comparison showed that AdaBoost was an effective classifier using the one-versus-the-rest mode of operation.",

keywords = "Image annotation 、 Content-based image retrieval、AdaBoost learning algorithm",

author = "Lin, {Wei Chao} and Chen, {Yan Ze} and Chen, {Shu Yuan}",

note = "Publisher Copyright: {\textcopyright} 2018 Newswood Limited. All rights reserved.; 2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018 ; Conference date: 14-03-2018 Through 16-03-2018",

year = "2018",

language = "英语",

series = "Lecture Notes in Engineering and Computer Science",

publisher = "Newswood Limited",

pages = "293--298",

editor = "Craig Douglas and Korsunsky Korsunsky and Oscar Castillo and Ao, {S. I.} and Feng, {David Dagan}",

booktitle = "Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018",

}

Lin, WC, Chen, YZ & Chen, SY 2018, Adaboost for concrete type of keywords annotation. in C Douglas, K Korsunsky, O Castillo, SI Ao & DD Feng (eds), Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018. Lecture Notes in Engineering and Computer Science, vol. 2233, Newswood Limited, pp. 293-298, 2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018, Hong Kong, Hong Kong, 14/03/18.

Adaboost for concrete type of keywords annotation. / Lin, Wei Chao; Chen, Yan Ze; Chen, Shu Yuan.
Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018. ed. / Craig Douglas; Korsunsky Korsunsky; Oscar Castillo; S. I. Ao; David Dagan Feng. Newswood Limited, 2018. p. 293-298 (Lecture Notes in Engineering and Computer Science; Vol. 2233).

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

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AU - Chen, Yan Ze

AU - Chen, Shu Yuan

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AB - The semantic gap presents an arduous task in semantic-based image retrieval investigations. In this paper, the author proposes the AdaBoost learning algorithm for large vocabulary classification. The main finding of this investigation is that using Gentle AdaBoost for image classification produced excellent results in terms of precision and the F-measure. With 190 concrete keywords categorisation, AdaBoost renders more keywords assignable and allows a significant improvement in all accuracy measures: precision, recall and F-measure. An AdaBoost vs. SVMs comparison showed that AdaBoost was an effective classifier using the one-versus-the-rest mode of operation.

KW - Image annotation 、 Content-based image retrieval、AdaBoost learning algorithm

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A2 - Douglas, Craig

A2 - Korsunsky, Korsunsky

A2 - Castillo, Oscar

A2 - Ao, S. I.

A2 - Feng, David Dagan

PB - Newswood Limited

T2 - 2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018

Y2 - 14 March 2018 through 16 March 2018

ER -

Adaboost for concrete type of keywords annotation

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