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A Review Study - In Image Retrieval Bridging Of Semantic Gap

Authors: Rajat Pratap; Arti Gautam; Annu Malik; Reshu Agarwal; Govind Kumar Rahul; Shylaja Karatangi;

A Review Study - In Image Retrieval Bridging Of Semantic Gap

Abstract

{"references": ["Enser, P. G., Sandom, C. J., Hare, J. S., and Lewis, P. H. (2007). Facing the reality of semantic image retrieval. Journal of Documentation, 63(4), 465- 481", "Kherfi, M.L., Ziou, D., and Bernardi, A. (2004). Image retrieval from the World Wide Web: issues, techniques, and systems. ACM Computing Surveys, 36(1), 35\u201367", "Liu, Y., Zhang, D., Lu, G., and Ying, W. (2007). A survey of content-based image retrieval with high-level semantics. In Journal of Pattern Recognition, 40(1), 262\u2013 282", "Ting, W. Su, Chen, J., Jier, J. and Lien, J. (2010). Region-based image retrieval system with heuristic preclustering relevance feedback. Expert Systems with Applications, 37(7), 4984-499", "Wong, R.C.F. and Leung, C.H.C. (2008). Automatic Semantic Annotation of Real-World Web Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(11), 1933-1945.", "Lin, W.-C., Oakes, M., and Tait, J. (2010). Improving image annotation via representative feature vector selection\", Neuro computing, 73, 1774\u20131782", "Shen, H. T. (2009). Speed up interactive image retrieval. VLDB Journal, 18(1), 465-474. Springer", "Santos, J. A., Ferreira, C. D., Torres, R., Gon\u00e7alves, M. A., and Lamparelli, R. A. C.( 2011) . A relevance feedback method based on genetic programming for classification of remote sensing images. Information Sciences, 181(13), 2671-2684", "Ferreira, C.D., Santos, J. A., Torres, R. S., Gon\u00e7alves, M.A., Rezende, R.C., and Fan W. (2011). Relevance Feedback based on Genetic Programming for Image Retrieval. Pattern Recognition Letters, 32(1), 27- 37", "Qi, X., and Han, T. (2007). Incorporating Multiple SVMs for Automatic Image Annotation. Pattern Recognition, 40(2), 728-741", "Wong, R.C.F. and Leung, C.H.C. (2008). Automatic Semantic Annotation of Real-World Web Images IEEE Transactions on pattern analysis and machine intelligence, 30(11), 1933- 1944", "Liua, J., Li, M., Liua Q., Lu, H., and Ma, S. (2009). Image annotation via graph learning. Journal of Pattern Recognition, 42, 218 \u2013 228", "Ganea, E. (2010). An Object Oriented Graph Approach for Image Representation and Query Based on Content. International Journal of Computer Science and Applications, 7 (1), 45 \u2013 59", "Kesorn, K., Poslad, S. (2009). Semantic Restructuring of Natural Language Image Captions to Enhance Image Retrieval. Journal of Multimedia, 4(5), 284-297", "Kingshy, E., Sychay, G., and Gang Wu, G. (2003). CBSA: Content-based Soft Annotation for Multimodal Image Retrieval using Bayes Point Machines. IEEE Transactions on Circuits and Systems for Video Technology, 3(1), 26 \u2013 38"]}

The linguistics gap is frequently viewed as a stimulating issue within the field of image retrieval analysis. This paper endeavors to allow a so much reaching survey and describe the foremost downside of content-based image retrieval i.e. linguistics gap downside and also the gift endeavors in semantic-based image recovery being created to attach it. At long last, seeable of existing innovations, a handful of promising future analysis directions is projected.

Keywords

Semantic Gap, Image Retrieval, Automatic Annotation, CBIR and Ontology, http://matjournals.com/journals.html

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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