UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 6
June-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIRFR06008


Registration ID:
501074

Page Number

37-44

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Title

Convolutional Neural Networks for Abnormality Detection: A Review

Abstract

The author suggests a computer-aided detection approach for identifying and identifying tumors and abnormalities in mammography images to minimize radiologists' costs and labor. We use deep convolutional neural networks (CNN) for automated object detection and classifier construction to enhance on traditional techniques. Deep CNN classifications can be learned directly on complete mammogram pictures in computer aided radiography because image features are lost during resizing only at embedding layer. We discuss our complex neural network-based technique for classifying brain magnetic resonance (MR) pictures into advantage of unexpected and appropriate classifications in this study. We recommend that our technique be used to detect lower and higher grade gliomas, cystic fibrosis, Alzheimer's disease, or healthy instances. There are 10 training layers within our network design, including 7 convolution operation and 3 fully linked layers. Using 95.7 percent accuracy, we got encouraging results on five types of brain pictures (classification job)

Key Words

Convolutional Neural Networks (CNN), Deep Learning, Detection, Mammography, X-Ray

Cite This Article

"Convolutional Neural Networks for Abnormality Detection: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.37-44, June-2018, Available :http://www.jetir.org/papers/JETIRFR06008.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Convolutional Neural Networks for Abnormality Detection: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp37-44, June-2018, Available at : http://www.jetir.org/papers/JETIRFR06008.pdf

Publication Details

Published Paper ID: JETIRFR06008
Registration ID: 501074
Published In: Volume 5 | Issue 6 | Year June-2018
DOI (Digital Object Identifier):
Page No: 37-44
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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