Publications

Export 36 results:
Filters: Author is Putzu, Lorenzo  [Clear All Filters]
2013
L. Putzu e 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, pagg 612 – 621.
L. Putzu e 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, pagg 99-106.
2014
C. Di Ruberto e 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, pagg 601 – 609.
L. Putzu, Caocci, G., e Di Ruberto, C., «Leucocyte classification for leukaemia detection using image processing techniques», Artificial Intelligence in Medicine, vol 62, pagg 179 – 191, 2014.
2015
C. Di Ruberto e Putzu, L., «Accurate blood cells segmentation through intuitionistic fuzzy set threshold», in Proceedings - 10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014, 2015, pagg 57 – 64.
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, Loddo, A., e 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, pagg 557 – 567.
C. Di Ruberto, Loddo, A., e 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, pagg 415 – 425, 2015.
2016
C. Di Ruberto e Putzu, L., A Feature Learning Framework for Histology Images Classification. 2016, pagg 37 – 48.
C. Di Ruberto, Loddo, A., e 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, pagg 1151 – 1160, 2016.
L. Putzu, Di Ruberto, C., e 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, pagg 570 – 581, 2016.
A. Loddo, Di Ruberto, C., e 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, pagg 15 – 23.
2017
A. Loddo, Putzu, L., Di Ruberto, C., e Fenu, G., «A Computer-Aided System for Differential Count from Peripheral Blood Cell Images», in Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016, 2017, pagg 112 – 118.
C. Di Ruberto, Loddo, A., e 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, pagg 345 – 356, 2017.
L. Putzu e 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, pagg 391 – 401, 2017.
2018
C. Di Ruberto, Putzu, L., e Rodriguez, G., «Fast and accurate computation of orthogonal moments for texture analysis», Pattern Recognition, vol 83, pagg 498 – 510, 2018.
L. Putzu, Piras, L., e 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.
S. Porcu, Loddo, A., Putzu, L., e 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, pagg 227 – 234.
2019
C. Di Ruberto, Loddo, A., e 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, pagg 47 – 58, 2019.
2020
L. Putzu, Piras, L., e 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, pagg 26995-27021, 2020.
C. Di Ruberto, Loddo, A., e Putzu, L., «Detection of red and white blood cells from microscopic blood images using a region proposal approach», Computers in Biology and Medicine, vol 116, 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. 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)

Pages