Paper Abstract and Keywords |
Presentation |
2010-05-14 14:45
An Analysis of the Impact of a Training Dataset Expansion for Generic Object Recognition Takumi Toyama, Koichi Kise (Osaka Prefecture Univ.) IE2010-40 PRMU2010-28 MI2010-28 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In the field of pattern recognition, it is well known that the contents of a training dataset affects the recognition performance.
Most datasets used in the field of generic object recognition have a somewhat small number of
samples per category. Thus, it is reasonable to think that we can acquire higher recognition performance by expanding the dataset.
Although several approaches have attempted to increase the number of samples, the amount of these increased samples is about ten thousands which can be increased more to acquire much higher recognition performance.
Thus, we collect hundred thousands of images and compare the recognition performance between the dataset with original size and the dataset which is expanded with our dataset expansion method.
In addition, we also analyze the impact of using different classifiers for these expanded datasets. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Generic object recognition / Dataset expansion / Filtering / Support Vector Machine / $k$-Nearest Neighbor / / / |
Reference Info. |
IEICE Tech. Rep., vol. 110, no. 27, PRMU2010-28, pp. 145-150, May 2010. |
Paper # |
PRMU2010-28 |
Date of Issue |
2010-05-06 (IE, PRMU, MI) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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IE2010-40 PRMU2010-28 MI2010-28 |
Conference Information |
Committee |
PRMU IE MI |
Conference Date |
2010-05-13 - 2010-05-14 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Chubu Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2010-05-PRMU-IE-MI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
An Analysis of the Impact of a Training Dataset Expansion for Generic Object Recognition |
Sub Title (in English) |
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Keyword(1) |
Generic object recognition |
Keyword(2) |
Dataset expansion |
Keyword(3) |
Filtering |
Keyword(4) |
Support Vector Machine |
Keyword(5) |
$k$-Nearest Neighbor |
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1st Author's Name |
Takumi Toyama |
1st Author's Affiliation |
Osaka Prefecture University (Osaka Prefecture Univ.) |
2nd Author's Name |
Koichi Kise |
2nd Author's Affiliation |
Osaka Prefecture University (Osaka Prefecture Univ.) |
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Speaker |
Author-1 |
Date Time |
2010-05-14 14:45:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
IE2010-40, PRMU2010-28, MI2010-28 |
Volume (vol) |
vol.110 |
Number (no) |
no.26(IE), no.27(PRMU), no.28(MI) |
Page |
pp.145-150 |
#Pages |
6 |
Date of Issue |
2010-05-06 (IE, PRMU, MI) |
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