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Published in:

Volume 7 Issue 3
March-2020
eISSN: 2349-5162

Unique Identifier

JETIRDP06007

Page Number

30-34

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Title

Deep Features Based Coral Reef Classifications Using Machine Learning

ISSN

2349-5162

Cite This Article

"Deep Features Based Coral Reef Classifications Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.30-34, March-2020, Available :http://www.jetir.org/papers/JETIRDP06007.pdf

Abstract

The Sea water is the source for a number of creatures. Among the creatures coral reefs are the one with 800 classes of species. It is a stimulating task to classify coral.Based upon its characteristics and features scientist grouped the coral reefs in to several classes. There are a number of machine learning algorithms implemented to inspect and group the coral species.The main aim of this work is to effectively use handcrafted features and deep features for classifying the coral classes. Here the feature descriptors such as Local Binary Pattern, Local Arc Pattern are proposed to excerpt the features of coral.The features retrieved by above methods are classified using KNN and Random Forest. EILAT dataset is used for above experiments.The outcomes which attained gives the effectiveness of the above methods.

Key Words

LBP, KNN, Random Forest, Local Arc Pattern.

Cite This Article

"Deep Features Based Coral Reef Classifications Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp30-34, March-2020, Available at : http://www.jetir.org/papers/JETIRDP06007.pdf

Publication Details

Published Paper ID: JETIRDP06007
Registration ID: 229377
Published In: Volume 7 | Issue 3 | Year March-2020
DOI (Digital Object Identifier):
Page No: 30-34
ISSN Number: 2349-5162

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Cite This Article

"Deep Features Based Coral Reef Classifications Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp30-34, March-2020, Available at : http://www.jetir.org/papers/JETIRDP06007.pdf




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