R. Delussu, Putzu, L., e Fumera, G.,
«An Empirical Evaluation of Cross-scene Crowd Counting Performance», in
Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP, Valletta - Malta, 2020, vol 4, pagg 373-380.
(527.29 KB) R. Delussu, Putzu, L., e Fumera, G.,
«Investigating Synthetic Data Sets for Crowd Counting in Cross-scene Scenarios», in
Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISAPP 2020, Valletta - Malta, 2020, vol 4, pagg 365-372.
(4.23 MB) L. Demetrio, Biggio, B., Lagorio, G., Roli, F., e Armando, A.,
«Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware»,
IEEE Transactions on Information Forensics and Security, vol 16, pagg 3469-3478, 2021.
L. Demetrio, Biggio, B., Lagorio, G., Roli, F., e Armando, A.,
«Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries», in
3rd Italian Conference on Cyber Security, ITASEC 2019, Pisa, Italy, 2019, vol 2315.
(801.85 KB) A. Demontis, Russu, P., Biggio, B., Fumera, G., e Roli, F.,
«On Security and Sparsity of Linear Classifiers for Adversarial Settings», in
Joint IAPR Int'l Workshop on Structural, Syntactic, and Statistical Pattern Recognition, Merida, Mexico, 2016, vol 10029 of LNCS, pagg 322-332.
(425.68 KB) A. Demontis, Biggio, B., Fumera, G., Giacinto, G., e Roli, F.,
«Infinity-norm Support Vector Machines against Adversarial Label Contamination»,
1st Italian Conference on CyberSecurity (ITASEC). Venice, Italy , pagg 106-115, 2017.
(504.93 KB) A. Demontis, Melis, M., Pintor, M., Jagielski, M., Biggio, B., Oprea, A., Nita-Rotaru, C., e Roli, F.,
«Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks», in
28th Usenix Security Symposium, Santa Clara, California, USA, 2019, vol 28th {USENIX} Security Symposium ({USENIX} Security 19), pag 321--338.
(1.09 MB) A. Demontis, Biggio, B., Fumera, G., e Roli, F.,
«Super-Sparse Regression for Fast Age Estimation From Faces at Test Time», in
18th Int'l Conf. on Image Analysis and Processing (ICIAP), Genova, Italy, 2015, vol Image Analysis and Processing (ICIAP 2015), pagg 551-562.
(678.7 KB) A. Demontis, Melis, M., Biggio, B., Fumera, G., e Roli, F.,
«Super-sparse Learning in Similarity Spaces»,
IEEE Computational Intelligence Magazine, vol 11, n° 4, pagg 36-45, 2016.
(555.22 KB) A. Demontis, Melis, M., Biggio, B., Maiorca, D., Arp, D., Rieck, K., Corona, I., Giacinto, G., e Roli, F.,
«Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection»,
IEEE Trans. Dependable and Secure Computing, vol 16, n° 4, pagg 711-724, 2019.
(3.61 MB) C. Di Ruberto, Fodde, G., e Putzu, L.,
«Comparison of statistical features for medical colour image classification»,
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol 9163. pagg 3 – 13, 2015.
C. Di Ruberto, Fodde, G., e Putzu, L.,
«On different colour spaces for medical colour image classification»,
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol 9256, pagg 477 – 488, 2015.