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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Skin Lesion Detection using Convolutional Neural Network
Authors Name: C.Rekha , R.Jegatha , P.Sharmila , A.Cibi
Unique Id: IJSDR2101015
Published In: Volume 6 Issue 1, January-2021
Abstract: Melanoma is the most destructive form of skin cancer. Early diagnosis of melanoma can be curable. At the same time accurate diagnosis is very essential because of the similarities of melanoma and benign lesions. Hence computerized recognition approaches are highly demanded for dermoscopy images. The main purpose of this project is to develop an automatic system to improve the classification performance of melanoma. The effectiveness of this framework is evaluated on ISBI 2016 Skin Lesion Analysis towards Melanoma Detection Challenge dataset. Initially the extraction of discriminate features is done with the help of Convolution Neural Network. ResNet-50 algorithm is used to classify every lesion in a dermoscopic image as a Benign or Melanoma. Results are found from classification with and without segmented images. This work performs a comparative evaluation of classification alone (using the entire image) against a combination of the two approaches (segmentation followed by classification) in order to assess which of them achieves better classification results. The proposed method would constitute a valuable support for physicians in every day clinical practice.
Keywords: CNN - Convolution Neural Network, AUC - Area under the curve, ISIC - International Skin Imaging Collaboration
Cite Article: "Skin Lesion Detection using Convolutional Neural Network", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 1, page no.102 - 107, January-2021, Available :http://www.ijsdr.org/papers/IJSDR2101015.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2101015
Registration ID:192832
Published In: Volume 6 Issue 1, January-2021
DOI (Digital Object Identifier):
Page No: 102 - 107
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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