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Diego Gragnaniello
Diego Gragnaniello
University of Salerno, Dept. of Computer Engineering, Electrical Engineering and Applied Mathematics
在 unisa.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
3912018
Do gans leave artificial fingerprints?
F Marra, D Gragnaniello, L Verdoliva, G Poggi
2019 IEEE conference on multimedia information processing and retrieval …, 2019
3362019
An investigation of local descriptors for biometric spoofing detection
D Gragnaniello, G Poggi, C Sansone, L Verdoliva
IEEE transactions on information forensics and security 10 (4), 849-863, 2015
2142015
LivDet iris 2017—Iris liveness detection competition 2017
D Yambay, B Becker, N Kohli, D Yadav, A Czajka, KW Bowyer, ...
2017 IEEE International Joint Conference on Biometrics (IJCB), 733-741, 2017
1932017
Fingerprint Liveness Detection based on Weber Local Image Descriptor
D Gragnaniello, G Poggi, C Sansone, L Verdoliva
IEEE Workshop on Biometric Measurements and Systems for Security and Medical …, 2013
1572013
Local contrast phase descriptor for fingerprint liveness detection
D Gragnaniello, G Poggi, C Sansone, L Verdoliva
Pattern Recognition 48 (4), 1050-1058, 2015
1552015
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
1462021
Image forgery localization through the fusion of camera-based, feature-based and pixel-based techniques
D Cozzolino, D Gragnaniello, L Verdoliva
2014 IEEE International Conference on Image Processing (ICIP), 5302-5306, 2014
141*2014
Image forgery detection through residual-based local descriptors and block-matching
D Cozzolino, D Gragnaniello, L Verdoliva
2014 IEEE international conference on image processing (ICIP), 5297-5301, 2014
1282014
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
1062020
Iris Liveness Detection for Mobile Devices based on local descriptors
D Gragnaniello, C Sansone, L Verdoliva
Pattern Recognition Letters, 2014
872014
The 1st competition on counter measures to finger vein spoofing attacks
P Tome, R Raghavendra, C Busch, S Tirunagari, N Poh, BH Shekar, ...
2015 international conference on biometrics (ICB), 513-518, 2015
762015
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
572018
Analysis of adversarial attacks against CNN-based image forgery detectors
D Gragnaniello, F Marra, G Poggi, L Verdoliva
2018 26th European Signal Processing Conference (EUSIPCO), 967-971, 2018
412018
Using iris and sclera for detection and classification of contact lenses
D Gragnaniello, G Poggi, C Sansone, L Verdoliva
Pattern Recognition Letters 82, 251-257, 2016
402016
A new unsupervised approach for segmenting and counting cells in high-throughput microscopy image sets
D Riccio, N Brancati, M Frucci, D Gragnaniello
IEEE journal of biomedical and health informatics 23 (1), 437-448, 2018
392018
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
Biologically-inspired dense local descriptor for indirect immunofluorescence image classification
D Gragnaniello, C Sansone, L Verdoliva
2014 1st Workshop on Pattern Recognition Techniques for Indirect …, 2014
332014
Perceptual quality-preserving black-box attack against deep learning image classifiers
D Gragnaniello, F Marra, G Poggi, L Verdoliva
Pattern Recognition Letters, 2021
312021
Retinal vessels segmentation based on a convolutional neural network
N Brancati, M Frucci, D Gragnaniello, D Riccio
Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2018
312018
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