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
Deep Learning based Video forgery detection using Tensor flow and CNN algorithm
Authors Name:
Shaikh Shorab
Unique Id:
IJSDR2211057
Published In:
Volume 7 Issue 11, November-2022
Abstract:
Computerized Videos duplicate move falsification location could be a slanting theme in interactive media crime lo- cation examination. Securing recordings and other computerized media from a modifying has turned into an reason of concern. Video duplicate move falsification has progressively gotten a form of cyber crime that’s utilized to utilizing recordings for various malevolent purposes, as an example, giving phony confirmations in courtrooms, spreading counterfeit bits of gossip, utilizing it to malign a private. A good deal of approaches is proposed for distinguishing the follows left by any phony caused due to the duplicate move activity. Right now, we direct a review on these current methodologies which are applied for the invention of du- plicate – move recordings and furthermore for the distinguishing proof fabrication within the pictures. In a very portion of these techniques, the difficulty of duplicate move video fabrication has been cared-for utilizing various procedures. Strategies, for instance, commotion buildup, movement and splendor slopes, optical stream strategies understand just piece of the whole issue. This review examinations the present arrangements and what they provide to handle this issue.
Keywords:
Information Security,Copy-move forgery detec- tion, Image forensics, Segmentation, Video Forgery Detection, Temporal Tampering, Estimation, Double Compression
Cite Article:
"Deep Learning based Video forgery detection using Tensor flow and CNN algorithm", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.345 - 348, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211057.pdf
Downloads:
000337067
Publication Details:
Published Paper ID: IJSDR2211057
Registration ID:202539
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 345 - 348
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
Facebook Twitter Instagram LinkedIn