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L. Putzu, Piras, L., and Giacinto, G., “Convolutional neural networks for relevance feedback in content based image retrieval: A Content based image retrieval system that exploits convolutional neural networks both for feature extraction and for relevance feedback”, Multimedia Tools and Applications, vol. 79, pp. 26995-27021, 2020.
L. Putzu and Di Ruberto, C., “White Blood Cells Identification and Classification from Leukemic Blood Image”, in PROCEEDINGS IWBBIO 2013: INTERNATIONAL WORK-CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, AV ANDALUCIA, 38, GRANADA, GRANADA 18014, SPAIN, 2013, pp. 99-106.
L. Putzu and Fumera, G., “An empirical evaluation of nuclei segmentation from H&E images in a real application scenario”, Applied Sciences (Switzerland), vol. 10, pp. 1-15, 2020.
L. Putzu and Di Ruberto, C., “Investigation of different classification models to determine the presence of leukemia in peripheral blood image”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 8156 LNCS, pp. 612 – 621.
L. Putzu, Caocci, G., and Di Ruberto, C., “Leucocyte classification for leukaemia detection using image processing techniques”, Artificial Intelligence in Medicine, vol. 62, pp. 179 – 191, 2014.
L. Putzu, Loddo, A., and Di Ruberto, C., “Invariant Moments, Textural and Deep Features for Diagnostic MR and CT Image Retrieval”, in Computer Analysis of Images and Patterns, Cham, 2021, pp. 287–297.
L. Putzu, Di Ruberto, C., and Fenu, G., “A mobile application for leaf detection in complex background using saliency maps”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10016 LNCS, pp. 570 – 581, 2016.
L. Putzu, Untesco, M., and Fumera, G., “Automatic Myelofibrosis Grading from Silver-Stained Images”, in Computer Analysis of Images and Patterns, Cham, 2021, pp. 195–205.
L. Putzu, Piras, L., and Giacinto, G., “Ten years of Relevance Score for Content Based Image Retrieval”, in 14th International Conference Machine Learning and Data Mining (MLDM), New York, 2018, vol. 10935.
L. Putzu and Di Ruberto, C., “Rotation invariant co-occurrence matrix features”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10484 LNCS, pp. 391 – 401, 2017.
S. Porcu, Loddo, A., Putzu, L., and Di Ruberto, C., “White blood cells counting via vector field convolution nuclei segmentation”, in VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2018, vol. 4, pp. 227 – 234.
N. Poh, Rattani, A., and Roli, F., “A Critical Analysis of Adaptive Biometric Systems”, IET Biometrics, 2012.
P. Piredda, Ariu, D., Biggio, B., Corona, I., Piras, L., Giacinto, G., and Roli, F., “Deepsquatting: Learning-based Typosquatting Detection at Deeper Domain Levels”, in 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017, vol. 10640 of LNCS, pp. 347-358. (1.21 MB)
L. Piras, Giacinto, G., and Paredes, R., “Passive-Aggressive Online Learning for Relevance Feedback in Content Based Image Retrieval”, in 2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM), Barcelona, Spain, 2013. (138.32 KB)
L. Piras and Giacinto, G., “Open issues on codebook generation in Image Classification tasks”, in 10th International Conference Machine Learning and Data Mining (MLDM), St. Petersburg, Russia, 2014, pp. 328-342. (229.92 KB)
L. Piras and Giacinto, G., “Neighborhood-Based Feature Weighting for Relevance Feedback in Content-Based Retrieval”, in 10th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), London, United Kingdom, 2009, pp. 238-241. (181.68 KB)
L. Piras, Giacinto, G., and Paredes, R., “Enhancing image retrieval by an Exploration-Exploitation approach”, in 8th International Conference Machine Learning and Data Mining (MLDM), Berlin, 2012, vol. 7376, pp. 355-365. (307.57 KB)
L. Piras and Giacinto, G., “Information Fusion in Content Based Image Retrieval: A Comprehensive Overview”, Information Fusion, vol. 37, pp. 50-60, 2017. (734.6 KB)
L. Piras, Tronci, R., Murgia, G., and Giacinto, G., “The PRA and AmILAB at ImageCLEF 2012 Photo Flickr Annotation Task”, in CLEF (Online Working Notes/Labs/Workshop), Rome, 2012. (540.05 KB)
L. Piras and Giacinto, G., “Unbalanced learning in Content-Based Image Classification and Retrieval”, in IEEE International Conference on Multimedia & Expo (ICME), Singapore, 2010. (177.33 KB)
L. Piras, Tronci, R., and Giacinto, G., “Diversity in ensembles of codebooks for visual concept detection”, in 17th Int. Conference on Image Analysis and Processing (ICIAP), Naples, Italy, 2013. (303.73 KB)
L. Piras and Giacinto, G., “K-Nearest Neighbors Directed Synthetic Images Injection”, in 11th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), Desenzano del Garda, Italy, 2010. (167.12 KB)
L. Piras and Giacinto, G., “Synthetic Pattern Generation for Imbalanced Learning in Image Retrieval”, Pattern Recognition Letters, vol. 33, p. 7, 2012. (236.64 KB)
L. Piras, Caputo, B., Dang-Nguyen, D. - T., Riegler, M., and Halvorsen, P., “Image Retrieval Evaluation in Specific Domains”, in Information Retrieval Evaluation in a Changing World - Lessons Learned from 20 Years of CLEF, 2019, pp. 275–305. (202.36 KB)
L. Piras and Giacinto, G., “Dissimilarity representation in multi-feature spaces for image retrieval”, in 16th Int. Conference on Image Analysis and Processing (ICIAP), Ravenna, Italy, 2011. (252.22 KB)

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