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A. Loddo e Putzu, L., «On the Effectiveness of Leukocytes Classification Methods in a Real Application Scenario», AI, vol 2, pagg 394–412, 2021.
C. Lobrano, Tronci, R., Giacinto, G., e Roli, F., «Dynamic Linear Combination of Two-Class Classifiers», in Lecture Notes in Computer Science, 2010, vol 6218, pagg 473-482.
C. Lobrano, Tronci, R., Giacinto, G., e Roli, F., «A Score Decidability Index for Dynamic Score Combination», in Pattern Recognition, International Conference on, Los Alamitos, CA, USA, 2010, pagg 69-72.
H. - Y. Lin e Biggio, B., «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
C. - T. Li e Satta, R., «On the Location-Dependent Quality of the Sensor Pattern Noise and Its Implication in Multimedia Forensics», in 4th International Conference on Imaging for Crime Detection and Prevention (ICDP 2011), London, United Kingdom, 2011. (399.99 KB)
C. - T. Li e Satta, R., «Empirical Investigation into the Correlation between Vignetting Effect and the Quality of Sensor Pattern Noise», IET Computer Vision, vol 6, n° 6, pagg 560-566, 2012.
E. Ledda, Putzu, L., Delussu, R., Loddo, A., e Fumera, G., «How Realistic Should Synthetic Images Be for Training Crowd Counting Models?», in Computer Analysis of Images and Patterns, Cham, 2021, pagg 46–56.
B. Lavi, Fumera, G., e Roli, F., «Multi-Stage Ranking Approach for Fast Person Re-Identification», IET Computer Vision, vol 12, n° 4, pag 7, 2018. (1.07 MB)
R. Labaca-Castro, Biggio, B., e Rodosek, G. Dreo, «Poster: Attacking Malware Classifiers by Crafting Gradient-Attacks That Preserve Functionality», in Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, New York, NY, USA, 2019, pagg 2565–2567.