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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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DTSTART:20191027T030000
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DTSTART:20190331T020000
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UID:calendar.18221.field_data.0@oba.diag.uniroma1.it
DTSTAMP:20260404T193125Z
CREATED:20190716T170406Z
DESCRIPTION:Nowadays\, with the prevalence of low-cost imaging devices (sma
 rtphones\, tablets\, camcorders\, digital cameras\, scanners\, wearable an
 d IoT devices)\, images and videos have become the main modalities of info
 rmation being exchanged in everyday life. The ever-increasing convenience 
 of image acquisition has facilitated instant distribution and sharing of m
 ultimedia on digital social platforms. In the meantime\, powerful media ed
 iting tools allow people to easily manipulate digital content for maliciou
 s or criminal ends\, up to create completely new and photorealistic image 
 and video with the use of sophisticated AI techniques. In response to this
  threat\, multimedia forensics community has produced a major research eff
 ort regarding source identification and image forgery detection. In fact\,
  in all cases where multimedia serves as critical evidence\, forensic tech
 nologies that help to determine the origin\, the authenticity of sources a
 nd integrity of multimedia content become essential in forensic investigat
 ions or in fake news debunking.In detail\, in this seminar forensic method
 ologies and tools employed so far to analyze digital evidences to ensure m
 edia authenticity will be outlined with special attention to the most prom
 ising solutions relying on Convolutional Neural Networks\; an in-depth foc
 us will be dedicated to realistic scenarios\, such as the spreading of mul
 timedia data over social networks. Finally\, an overview of the recent tre
 nds and evolution will be provided giving an insight on new security issue
 s related to deepfakes and computer generated images with GAN.
DTSTART;TZID=Europe/Paris:20190718T100000
DTEND;TZID=Europe/Paris:20190718T100000
LAST-MODIFIED:20191008T082735Z
LOCATION:aula A7
SUMMARY:Strategies for Countering Fake Information: new trends in multimedi
 a authenticity verification and source identification - Irene Amerini\n\n
 \n  \n  \n\n    \n\n\nIrene\n\n\nAmerini  \n\n  \n\n    \n\n\n\n\n\nProfes
 sore associato\n\n\npagina personale\n\nstanza: \n\nB215\n\ntelefono: \n\n
 +39 0677274044  \n\n  \n\n    \n\nBiografia: \n\n\n\nIrene Amerini is Asso
 ciate Professor at the Department of Computer\, Control and Management Eng
 ineering A. Ruberti of Sapienza University of Rome\, Italy where she is le
 ading the Computer VIsion and Multimedia Forensics Research Team at ALCORL
 ab.\n\n\nFrom 2019-2022\, she was an Assistant Professor at DIAG\, Sapienz
 a University of Rome and previously a postdoctoral researcher at the Image
  Forensics and Security Lab\, Media Integration and Communication Center\,
  University of Florence (Italy). In 2018 she obtained a Visiting Research 
 Fellowship at Charles Sturt University (Australia) offered by the Australi
 an Government – Department of Education and Training through the Endeavour
  Scholarship & Fellowship program and the Italian Habilitation for Associa
 te Professor in Computer Science and Telecommunications.\n\n\nIn 2010 she 
 spent part of her PhD course at the Digital Data Embedding Laboratory\, De
 partment of Electrical and Computer Engineering\, Binghamton University (U
 S). In 2011 she received the Ph.D. in computer engineering\, multimedia an
 d telecommunication from the University of Florence (Italy) with the thesi
 s “Image forensics: source identification and tampering detection”.\n\n\nI
 n 2019 she co-organized the Woman In Computer Vision Workshop (WiCV) at CV
 PR 2019 in Long Beach\, California\, in 2020 the Woman In Computer Vision 
 Workshop (WiCV) at ECCV\, the W4PR (Woman at ICPR Workshop) in conjunction
  with ICPR 2021 and of the of the VERIMEDIA workshop in conjuction with IJ
 CNN July 2025.\n\n\nShe is currently a member of the IEEE Forensics and Se
 curity Technical Committee (IFS-TC)\, EURASIP TAC Biometrics\, Data Forens
 ics\, and Security and IAPR TC6 - Computational Forensics Committee and Se
 nior Area Editor (S-AE) for the SPS Signal Processing Letters (SPL) May 20
 25-2027.\n\n\nHer main research activities include computer vision\, patte
 rn recognition\, adversarial machine learning and multimedia forensics.\n
 \n\n \n\n\nList of publications on dblp or Google scholar\n\n\nEmail: amer
 ini AT diag.uniroma1.it\n\n\nWebsite/Teaching\n\n\nInteressi di ricerca: 
 \n\nMultimedia forensics and deepfake analysis\nMachine learning and deep 
 learning for image and video analysis\nDigital image and video processing
 \nAdversarial machine learning/deep learning\nComputer vision and monocula
 r depth estimation\n\n\nqualifica_rr: \n\nAssociate professors
URL;TYPE=URI:http://oba.diag.uniroma1.it/node/18221
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