Publications

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2018
R. Soleymani, Granger, E., e Fumera, G., «Progressive Boosting for Class Imbalance and Its Application to Face Re-Identification», Expert Systems With Applications, vol 101, pag 21, 2018. (1.11 MB)
2019
A. Carcangiu, Spano, L. Davide, Fumera, G., e Roli, F., «DEICTIC: a Compositional and Declarative Gesture Description based on Hidden Markov Model», International Journal of Human-Computer Studies, vol 122, pag 20, 2019. (1.69 MB)
2020
A. Sotgiu, Demontis, A., Melis, M., Biggio, B., Fumera, G., Feng, X., e Roli, F., «Deep Neural Rejection against Adversarial Examples», EURASIP Journal on Information Security, vol 5, 2020.
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)
L. Putzu e Fumera, G., «An empirical evaluation of nuclei segmentation from H&E images in a real application scenario», Applied Sciences (Switzerland), vol 10, pagg 1-15, 2020.
R. Soleymani, Granger, E., e Fumera, G., «F-Measure Curves: A Tool to Visualize Classifier Performance Under Imbalance», Pattern Recognition, vol 100, pag 107146, 2020. (3.15 MB)
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)
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)
2021
L. Putzu, Untesco, M., e Fumera, G., «Automatic Myelofibrosis Grading from Silver-Stained Images», in Computer Analysis of Images and Patterns, Cham, 2021, pagg 195–205.
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.
2022
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.
E. Ledda, Putzu, L., Delussu, R., Fumera, G., e Roli, F., «On the Evaluation of Video-Based Crowd Counting Models», Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol 13233 LNCS. pagg 301 – 311, 2022.
R. Delussu, Putzu, L., e Fumera, G., «Scene-specific Crowd Counting Using Synthetic Training Images», Pattern Recognition, vol 124, 2022. (3.14 MB)

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