Publications

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D. - T. Dang-Nguyen, Piras, L., Giacinto, G., Boato, G., e De Natale, F. G. B., «Multimodal Retrieval with Diversification and Relevance Feedback for Tourist Attraction Images», ACM Transactions on Multimedia Computing, Communications, and Applications, vol 13, n° 4, 2017. (5.94 MB)
D. - T. Dang-Nguyen, Piras, L., Riegler, M., Zhou, L., Lux, M., Tran, M. - T., Le, T. - K., Ninh, V. - T., e Gurrin, C., «Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval», in Working Notes of {CLEF} 2019 - Conference and Labs of the Evaluation Forum, Lugano, Switzerland, September 9-12, 2019., 2019. (4.58 MB)
D. - T. Dang-Nguyen, Piras, L., Giacinto, G., Boato, G., e De Natale, F. G. B., «A Hybrid Approach for Retrieving Diverse Social Images of Landmarks», in IEEE International Conference on Multimedia & Expo (ICME), Torino, 2015. (1.16 MB)
D. - T. Dang-Nguyen, Piras, L., Riegler, M., Zhou, L., Lux, M., e Gurrin, C., «Overview of ImageCLEFlifelog 2018: Daily Living Understanding and Lifelog Moment Retrieval», in Working Notes of {CLEF} 2018 - Conference and Labs of the Evaluation Forum, Avignon, France, September 10-14, 2018., 2018. (2.01 MB)
S. Kumar Dash, Suarez-Tangil, G., Khan, S., Tam, K., Ahmadi, M., Kinder, J., e Cavallaro, L., «DroidScribe: Classifying Android Malware Based on Runtime Behavior», in Mobile Security Technologies (MoST 2016), 2016. (571.22 KB)
R. Delussu, Putzu, L., e Fumera, G., «Scene-specific Crowd Counting Using Synthetic Training Images», Pattern Recognition, vol 124, 2022. (3.14 MB)
R. Delussu, Putzu, L., e Fumera, G., «On the Effectiveness of Synthetic Data Sets for Training Person Re-identification Models», in Proceedings - International Conference on Pattern Recognition, 2022, vol 2022-August, pagg 1208 – 1214.
R. Delussu, Putzu, L., Fumera, G., e Roli, F., «Online Domain Adaptation for Person Re-Identification with a Human in the Loop», in 25th International Conference on Pattern Recognition, {ICPR} 2020, Virtual Event / Milan, Italy, January 10-15, 2021, 2020, pagg 3829–3836. (770.02 KB)
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)
L. Demetrio, Coull, S. E., Biggio, B., Lagorio, G., Armando, A., e Roli, F., «Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection», ACM Trans. Priv. Secur., vol 24, 2021.
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)
M. A. A. Dewan, Granger, E., Marcialis, G. L., Sabourin, R., e Roli, F., «Adaptive Appearance Model Tracking for Still-to-Video Face Recognition», Pattern Recognition, vol 49, n° 1, 2016. (6.51 MB)
M. A. A. Dewan, Granger, E., Sabourin, R., Roli, F., e Marcialis, G. L., «A comparison of adaptive appearance methods for tracking faces in video surveillance», in 5th International Conference on Imaging for Crime Detection and Prevention (ICDP-13), 2013.
M. A. A. Dewan, Granger, E., Sabourin, R., Marcialis, G. L., e Roli, F., «Video Face Recognition From A Single Still Image Using an Adaptive Appearance Model Tracker», in IEEE Symposium Series on Computational Intelligence: IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM 2015), 2015, pagg 192-202. (533.82 KB)
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.
C. Di Ruberto e Putzu, L., A Feature Learning Framework for Histology Images Classification. 2016, pagg 37 – 48.

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