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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

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Volume 9 | Issue 4

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Paper Title:	Survey on Deep Learning Method for Designing Text Based Captcha
Authors Name:	MALAVIKA R , MANJUSHA NAIR S
Unique Id:	IJSDR1903081
Published In:	Volume 4 Issue 3, March-2019
Abstract:	Since captcha’s discovery, it is the most widely used security tool. They are of many types. Text based captchas are most commonly used. Large type of early easy captchas were easily infiltrated. After many number of modifications and changes ,existing types came into existence. There are different resistive techniques like Crowding Characters Together (CCT), Noise arcs, Complicated backgrounds ,Hollow schemes and Two layer structures, but all of these have drawbacks and can be broken. Here we are trying to design an effective text captcha that resist the existing attacks against captcha. Captcha is based on two principle, anti segmentation and anti recognition. Segmentation makes a captcha weak. The proposed method to design captcha is fast and effective with deep learning techniques.
Keywords:	deep learning, convolutional neural network, VGGNet, Neural style transfer
Cite Article:	"Survey on Deep Learning Method for Designing Text Based Captcha", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 3, page no.477 - 480, March-2019, Available :http://www.ijsdr.org/papers/IJSDR1903081.pdf
Downloads:	000337067
Publication Details:	Published Paper ID: IJSDR1903081 Registration ID:190259 Published In: Volume 4 Issue 3, March-2019 DOI (Digital Object Identifier): Page No: 477 - 480 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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