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Multi technique amalgamation for enhanced information identification with content based image data

Overview of attention for article published in SpringerPlus, December 2015
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  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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1 tweeter

Citations

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5 Dimensions

Readers on

mendeley
8 Mendeley
Title
Multi technique amalgamation for enhanced information identification with content based image data
Published in
SpringerPlus, December 2015
DOI 10.1186/s40064-015-1515-4
Pubmed ID
Authors

Rik Das, Sudeep Thepade, Saurav Ghosh

Abstract

Image data has emerged as a resourceful foundation for information with proliferation of image capturing devices and social media. Diverse applications of images in areas including biomedicine, military, commerce, education have resulted in huge image repositories. Semantically analogous images can be fruitfully recognized by means of content based image identification. However, the success of the technique has been largely dependent on extraction of robust feature vectors from the image content. The paper has introduced three different techniques of content based feature extraction based on image binarization, image transform and morphological operator respectively. The techniques were tested with four public datasets namely, Wang Dataset, Oliva Torralba (OT Scene) Dataset, Corel Dataset and Caltech Dataset. The multi technique feature extraction process was further integrated for decision fusion of image identification to boost up the recognition rate. Classification result with the proposed technique has shown an average increase of 14.5 % in Precision compared to the existing techniques and the retrieval result with the introduced technique has shown an average increase of 6.54 % in Precision over state-of-the art techniques.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Other 1 13%
Lecturer > Senior Lecturer 1 13%
Professor 1 13%
Researcher 1 13%
Other 0 0%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Biochemistry, Genetics and Molecular Biology 1 13%
Unknown 4 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 January 2016.
All research outputs
#3,383,522
of 6,900,838 outputs
Outputs from SpringerPlus
#716
of 1,666 outputs
Outputs of similar age
#143,767
of 283,204 outputs
Outputs of similar age from SpringerPlus
#92
of 325 outputs
Altmetric has tracked 6,900,838 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,666 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 283,204 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 325 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.