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Meta Analysis and Verification on Automated Image Tagging Techniques

S.Khoria 1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 478-488, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.478488

Online published on Jan 31, 2019

Copyright © S.Khoria . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.Khoria, “Meta Analysis and Verification on Automated Image Tagging Techniques,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.478-488, 2019.

MLA Style Citation: S.Khoria "Meta Analysis and Verification on Automated Image Tagging Techniques." International Journal of Computer Sciences and Engineering 7.1 (2019): 478-488.

APA Style Citation: S.Khoria, (2019). Meta Analysis and Verification on Automated Image Tagging Techniques. International Journal of Computer Sciences and Engineering, 7(1), 478-488.

BibTex Style Citation:
@article{_2019,
author = {S.Khoria},
title = {Meta Analysis and Verification on Automated Image Tagging Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {478-488},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3529},
doi = {https://doi.org/10.26438/ijcse/v7i1.478488}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.478488}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3529
TI - Meta Analysis and Verification on Automated Image Tagging Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - S.Khoria
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 478-488
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

Automatic image tagging is an active topic of research in computer vision and pattern recognition. There is a huge urge in the Computer Vision community today to find ways to automatically annotate images. Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords. Among them Support Vector Machines (SVMs) have been used extensively due to their generalization properties.

Key-Words / Index Term

Component, Formatting, Style, Styling, Insert (key words)

References

[1] Dengsheng Zhang, Md. Monirul Islam, Guojun Lu. “A review on automatic image annotation techniques” .(2012)
[2] Nasullah Khalid Alham, Maozhen Li , Yang Liu, Suhel Hammoud . “A MapReduce-based distributed SVM algorithm for automatic image annotation” .
[3] Minmin Chen, Alice Zheng, and Kilian Q. Weinberger, “Fast Image Tagging”.
[4] A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain . “Content-based image retrieval at the end of the early years . Pattern Analysis and Machine Intelligence, IEEE”.
[5] X. Qi and Y. Han. “Incorporating multiple svms for automatic image annotation . Pattern Recognition”, 40(2):728–741, February 2007.
[6] A. Yavlinsky, E. Schofield, and S. Rger . “Automated image annotation using global features and robust nonparametric density estimation”. In International Conference on Image and Video Retrieval, pages 507–517. Springer, 2005.
[7] O. Chapelle, P. Haffner, and V. N. Vapnik. “Support vector machines for histogram-based image classification”. Neural Networks, IEEE Transactions on, 10(5):1055–1064, 1999.
[8] V. Lavrenko, R. Manmatha, and J. Jeon. “A model for learning the semantics of pictures”. In in NIPS. MIT Press, 2003.
[9] Ying Liua,, Dengsheng Zhanga, Guojun Lua, Wei-Ying Ma, “A survey of content-based image retrieval with high-level semantics”.
[10] Tanveer J. Siddiqui , “Bridging the Semantic Gap”.
[11] Aanchan K Mohan and Marwan A.Torki, “Automatic Image Annotation using Neural Networks”.
[12]Alpesh Dabhi, Bhavesh Prajapati , “A Neural Network Model for Automatic Image Annotation and Annotation Refinement”: A survey 2014 IJEDR | Volume 2, Issue 1 43
[13]Suman Tatiraju, Avi Mehta , “Image Segmentation using k-means clustering, EM and Normalized Cuts”
[14]Sarthak panda, ”Color Image Segmentation Using K-means Clustering and Thresholding Technique” (march 2015)
[15] Dhatri Pandya1, Prof. Bhumika Shah, “Comparative Study on Automatic Image Annotation” (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 3, March 2014)
[16] P. Duygulu, K. Barnard, N. de Freitas, D. Forsyth,2002. "Object recognition as machine translation: learning a lexicon for a fixed image vocabulary", In Seventh European Conference on Computer Vision (ECCV), Vol. 4, pp. 97-112.
[17] Reena Pagare and Anita Shinde , “A study on Image Annotation Techniques”, International Journal of Computer Applications Volume 37-No6. January 2012.
[18] Lei Wu Member,IEEE Rong Jin, Anil K. Jain, Fellow, IEEE , “Tag Completion for Image Retrieval”.
[19] Dongping Tian , “Support vector machine for Automatic Image Annotation” International Journal of Hybrid Information Technology Vol.8 No.11(2015).
[20]Dataset : http://www.ci.gxnu.edu.cn/cbir/Dataset.aspx
[21]Attributes: http://sci2s.ugr.es/keel/dataset/data/multilabel/corel5k-names.txt