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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

Unique Identifier

JETIRAB06065

Page Number

372-375

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Title

A Review on Deep Learning Based Object Detection and Part Localization

ISSN

2349-5162

Cite This Article

"A Review on Deep Learning Based Object Detection and Part Localization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.372-375, February-2019, Available :http://www.jetir.org/papers/JETIRAB06065.pdf

Abstract

The rapid growth of image data leads to the need of research and development of image retrieval. Compared to normal image, fine grained images are difficult to classify. Recognizing objects in fine grained domains can be extremely challenging task due to subtle differences and variations in poses, scales and rotations between same species. Deep Learning has recently achieved superior performance on many tasks such as image classification, object detection and neural language processing. In this survey we mainly focus on the object detection, semantic part localization and feature extraction which can facilitate fine grained categorization

Key Words

fine grained images;Deep Learning; object detection;part localization

Cite This Article

"A Review on Deep Learning Based Object Detection and Part Localization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp372-375, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06065.pdf

Publication Details

Published Paper ID: JETIRAB06065
Registration ID: 197824
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier):
Page No: 372-375
ISSN Number: 2349-5162

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Cite This Article

"A Review on Deep Learning Based Object Detection and Part Localization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp372-375, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06065.pdf




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