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Francesco Marra
Francesco Marra
在 unina.it 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Detection of gan-generated fake images over social networks
F Marra, D Gragnaniello, D Cozzolino, L Verdoliva
2018 IEEE conference on multimedia information processing and retrieval …, 2018
3772018
Do gans leave artificial fingerprints?
F Marra, D Gragnaniello, L Verdoliva, G Poggi
2019 IEEE conference on multimedia information processing and retrieval …, 2019
3232019
Incremental learning for the detection and classification of gan-generated images
F Marra, C Saltori, G Boato, L Verdoliva
2019 IEEE international workshop on information forensics and security (WIFS …, 2019
1452019
Are GAN generated images easy to detect? A critical analysis of the state-of-the-art
D Gragnaniello, D Cozzolino, F Marra, G Poggi, L Verdoliva
2021 IEEE international conference on multimedia and expo (ICME), 1-6, 2021
1302021
A full-image full-resolution end-to-end-trainable CNN framework for image forgery detection
F Marra, D Gragnaniello, L Verdoliva, G Poggi
IEEE Access 8, 133488-133502, 2020
952020
Blind PRNU-based image clustering for source identification
F Marra, G Poggi, C Sansone, L Verdoliva
IEEE Transactions on Information Forensics and Security 12 (9), 2197-2211, 2017
932017
A deep learning approach for iris sensor model identification
F Marra, G Poggi, C Sansone, L Verdoliva
Pattern Recognition Letters 113, 46-53, 2018
782018
A study of co-occurrence based local features for camera model identification
F Marra, G Poggi, C Sansone, L Verdoliva
Multimedia Tools and Applications 76, 4765-4781, 2017
652017
On the vulnerability of deep learning to adversarial attacks for camera model identification
F Marra, D Gragnaniello, L Verdoliva
Signal Processing: Image Communication 65, 240-248, 2018
552018
Evaluation of residual-based local features for camera model identification
F Marra, G Poggi, C Sansone, L Verdoliva
International Workshop on Recent Advances in Digital Security: Biometrics …, 2015
522015
Analysis of adversarial attacks against CNN-based image forgery detectors
D Gragnaniello, F Marra, G Poggi, L Verdoliva
European Signal Processing Conference (EUSIPCO), 2018
412018
Combining PRNU and noiseprint for robust and efficient device source identification
D Cozzolino, F Marra, D Gragnaniello, G Poggi, L Verdoliva
EURASIP Journal on Information Security 2020, 1-12, 2020
362020
Perceptual quality-preserving black-box attack against deep learning image classifiers
D Gragnaniello, F Marra, L Verdoliva, G Poggi
Pattern Recognition Letters 147, 142-149, 2021
312021
Correlation clustering for PRNU-based blind image source identification
F Marra, G Poggi, C Sansone, L Verdoliva
2016 IEEE International Workshop on Information Forensics and Security (WIFS …, 2016
222016
Counter-forensics in machine learning based forgery detection
F Marra, G Poggi, F Roli, C Sansone, L Verdoliva
Media Watermarking, Security, and Forensics 2015 9409, 181-191, 2015
212015
Detection of AI-generated synthetic faces
D Gragnaniello, F Marra, L Verdoliva
Handbook of digital face manipulation and detection: From deepfakes to …, 2022
192022
PRNU-based forgery localization in a blind scenario
D Cozzolino, F Marra, G Poggi, C Sansone, L Verdoliva
Image Analysis and Processing-ICIAP 2017: 19th International Conference …, 2017
152017
Attacking the triangle test in sensor-based camera identification
F Marra, F Roli, D Cozzolino, C Sansone, L Verdoliva
ICIP, 5307-5311, 2014
142014
Virtual special issue on advances in digital security: Biometrics and forensics
D Gragnaniello, CT Li, F Marra, D Riccio
Pattern Recognition Letters 159, 220-221, 2022
32022
Guest editorial: Adversarial deep learning in biometrics & forensics
R Chellappa, D Gragnaniello, CT Li, F Marra, R Singh
Computer Vision and Image Understanding 208, 103227, 2021
12021
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