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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.
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.
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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.
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C. Di Ruberto, Loddo, A., and Putzu, L., “Special Issue on Image Processing Techniques for Biomedical Applications”, Applied Sciences (Switzerland), vol. 12, 2022.
R. Delussu, Putzu, L., and Fumera, G., “Scene-specific Crowd Counting Using Synthetic Training Images”, Pattern Recognition, vol. 124, 2022. (3.14 MB)
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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.
A. Loddo and Putzu, L., “On the Reliability of CNNs in Clinical Practice: A Computer-Aided Diagnosis System Case Study”, Applied Sciences (Switzerland), vol. 12, 2022.
C. Di Ruberto, Loddo, A., and Putzu, L., “A region proposal approach for cells detection and counting from microscopic blood images”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11752 LNCS, pp. 47 – 58, 2019.
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C. Di Ruberto, Loddo, A., and Putzu, L., “On The Potential of Image Moments for Medical Diagnosis”, Journal of Imaging, vol. 9, 2023.
A. Loddo, Di Ruberto, C., and Putzu, L., “Peripheral blood image analysis”, in VISIGRAPP 2016 - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Doctoral Consortium, 2016, pp. 15 – 23.
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R. Delussu, Putzu, L., Fumera, G., and 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, pp. 3829–3836. (770.02 KB)
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C. Di Ruberto, Loddo, A., and Putzu, L., “A multiple classifier learning by sampling system for white blood cells segmentation”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9257, pp. 415 – 425, 2015.
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.
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C. Di Ruberto, Loddo, A., and Putzu, L., “A leucocytes count system from blood smear images: Segmentation and counting of white blood cells based on learning by sampling”, Machine Vision and Applications, vol. 27, pp. 1151 – 1160, 2016.
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.
C. Di Ruberto, Loddo, A., and Putzu, L., “Learning by sampling for white blood cells segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9279, pp. 557 – 567.
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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.
R. Delussu, Putzu, L., and 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, pp. 365-372. (4.23 MB)
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.
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E. Ledda, Putzu, L., Delussu, R., Loddo, A., and Fumera, G., “How Realistic Should Synthetic Images Be for Training Crowd Counting Models?”, in Computer Analysis of Images and Patterns, Cham, 2021, pp. 46–56.
C. Di Ruberto, Loddo, A., and Putzu, L., “Histological image analysis by invariant descriptors”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10484 LNCS, pp. 345 – 356, 2017.
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C. Di Ruberto and Putzu, L., A Feature Learning Framework for Histology Images Classification. 2016, pp. 37 – 48.
C. Di Ruberto and Putzu, L., “A fast leaf recognition algorithm based on SVM classifier and high dimensional feature vector”, in VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014, vol. 1, pp. 601 – 609.
C. Di Ruberto, Putzu, L., and Rodriguez, G., “Fast and accurate computation of orthogonal moments for texture analysis”, Pattern Recognition, vol. 83, pp. 498 – 510, 2018.
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E. Ledda, Putzu, L., Delussu, R., Fumera, G., and 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. pp. 301 – 311, 2022.

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