MACHINE LEARNING SYSTEMS IN IMAGE MANIPULATION AND FAKE DETECTION.
Image processing is leading in some of the important areas like science and technology, biological, agriculture, face recognition and other fields. The main aim of machine learning is to improve or compress the image data. It is used to minimise a loss or cost function by optimising differentiable p...
| Publicado en: | Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 2627 - 2634 |
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| Autores principales: | , , , , , |
| Formato: | pictorial Journal Article |
| Publicado: |
Turkish Journal of Physiotherapy & Rehabilitation
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151006277&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151006277 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13008757 YU1 jtl: Turkish Journal of Physiotherapy Rehabilitation issn: 13008757 maglogo: N pubinfo: dt: 2021 vid: 32 iid: 2 pid: 20392 pub: Turkish Journal of Physiotherapy & Rehabilitation place: Kizilay/ Ankara, <Blank> artinfo: ui: 151006277 151006277 151006277 151006277 ppf: 2627 ppct: 7 formats: fmt: @attributes: type: P tig: atl: MACHINE LEARNING SYSTEMS IN IMAGE MANIPULATION AND FAKE DETECTION. aug: au: PAVAN, ABBURI M. N. S. P. RAJASEKARAN, ARUN SEKAR GEETHA, B. T. V., RADHAMANI SUBRAMANIAN, MUTHUKUMAR PERTI, ASHWIN affil: Department of ECE, GMR Institute of Technology, GMR Nagar, Rajam - 532 127, Andhra Pradesh, India sug: subj: Deception Prevention and Control Digital Imaging Image Processing, Computer Assisted Methods Machine Learning Neural Networks (Computer) Health Care Industry Artificial Intelligence Military Services Decision Trees Metadata ab: Image processing is leading in some of the important areas like science and technology, biological, agriculture, face recognition and other fields. The main aim of machine learning is to improve or compress the image data. It is used to minimise a loss or cost function by optimising differentiable parameters. As a result of combining these two, a greater understanding of image processing has emerged. On other hand improving the image data in machine learning is one of the factors on other hand Image are one of the most common sharing things on the internet. In this emerging era many fake images are also sharing with the real images. Forging the images leads to the cybercrimes, So the area of detecting forging images is difficult task. The tampered images are identified using the neural networks that recognizes a section of an original image that has been manipulated. The false content in a fake image has a different compression ratio than the original image that can be identified by using Error Level Analysis. pubtype: Academic Journal doctype: pictorial Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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