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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19457
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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| Paper Title: | Detection of underwater images of fish-using feature learning technique |
| Authors Name: | BASAVARAJA G C , VENKATA SUMANA C H |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_170284
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| Published Paper Id: | IJRTI1705059 |
| Published In: | Volume 2 Issue 5, May-2017 |
| DOI: | |
| Abstract: | Live fish acknowledgment is a standout amongst the most vital component of fisheries review applications. In fisheries overview handle a lot of information are quickly obtained. Not quite the same as general situations, difficulties to submerged picture acknowledgment are posted by poor picture quality, uncontrolled question and condition and additionally trouble in obtaining agent tests. Additionally, most existing element extraction methods are thwarted from computerization because of including human supervision. Towards this end, a submerged fish acknowledgment structure is suggested that comprise of a completely unsupervised element learning procedure and a mistake strong classifier and guarantee to get great picture quality. Protest parts introduced in view of saliency and unwinding naming to match question part accurately. A non-inflexible part model is then learned in light of wellness, division and separation criteria. MATLAB R2012b is favored for reenacting the said work. Some other MATLAB variants higher than MATLAB 2010 is prescribed because of its inserted with more numerical counts. |
| Keywords: | Feature learning, fish species identification, protest acknowledgment, submerged symbolism, unsupervised learning |
| Cite Article: | "Detection of underwater images of fish-using feature learning technique", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 5, page no.317 - 319, May-2017, Available :http://www.ijrti.org/papers/IJRTI1705059.pdf |
| Downloads: | 000205177 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI1705059
Registration ID:170284
Published In: Volume 2 Issue 5, May-2017
DOI (Digital Object Identifier):
Page No: 317 - 319 Country: DAVANGERE, KARNATAKA, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI1705059 Published Paper PDF: https://www.ijrti.org/papers/IJRTI1705059 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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