Video Tampering Localisation Using Features Learned From Authentic Content

Neural Computing and Applications - United Kingdom
doi 10.1007/s00521-019-04272-z
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

A Review of Digital Video Tampering: From Simple Editing to Full Synthesis

Digital Investigation
Information SystemsMedical Laboratory TechnologyComputer Science ApplicationsForensic MedicinePathologyLaw
2019English

Video Content on the Internet: Features of Audience Consumption

Theoretical and Practical Issues of Journalism
2019English

Using Video as an Authentic Material in Improving Students Writing Ability

International Journal of Humanities and Innovation (IJHI)
2018English

An Overview of Digital Video Tampering Detection Using Passive Methods and D-Hash Algorithm

International Journal of Engineering and Technology(UAE)
ArchitectureHardwareEngineeringChemical EngineeringBiotechnologyEnvironmental EngineeringComputer Science
2018English

Video Summarization Using Deep Semantic Features

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2017English

Video Game Localisation/ Localización De Videojuegos

TRANS. Revista de Traductologia
LinguisticsLanguage
2011English

Highlighting Image Tampering Using Statistical Quality Evaluation

International Journal of Computing, Communication and Instrumentation Engineering
2016English

Omnidirectional Video in Museums – Authentic, Immersive and Entertaining

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2018English

Detecting Informative Frames From Wireless Capsule Endoscopic Video Using Color and Texture Features

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2008English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy