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Corso di laurea in

Ingegneria industriale (elettrica, gestionale, meccanica)

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Simone PALAZZO

Ricercatore di Sistemi di elaborazione delle informazioni [ING-INF/05]
Contatti

Ufficio: Via S. Sofia, 102 - Laboratori Mednetna
Email: simone.palazzo@unict.it

Orario di ricevimento
Mercoledì e giovedì dalle 12:00 alle 13:00
ENGLISH VERSIONSTUDIUMAREA RISERVATA

Nel 2007 consegue la Laurea in Ingegneria Informatica (110/110 e lode) presso l'Università degli Studi di Catania, e nel 2010 la Laurea Magistrale in Ingegneria Informatica (110/110 e lode), presso lo stesso ateneo. Successivamente a quest'ultima svolge un periodo di formazione presso il centro di ricerca JET-EFDA (Culham, Oxfordshire, UK), risultando vincitore di una borsa di studio promossa dall'Ambasciata italiana a Londra.  Nel 2017 consegue il dottorato di ricerca presso l'Università di Catania, presentando una tesi dal titolo "Hybrid Human-Machine Vision Systems for Automated Object Segmentation and Categorization".

Tra il 2017 al 2020 svolge attività di assegnista di ricerca presso l'Università di Catania. Dal marzo 2020 è ricercatore (RTDA) nello stesso ateneo, dove svolge attività didattica e scientifica presso il Dipartimento di Ingegneria Elettrica, Elettronica ed Informatica (DIEEI) nel settore "Sistemi di Elaborazione delle Informazioni" (ING-INF/05). Passa al ruolo di RTDB a settembre 2022.

Nel 2018 ottiene l’abilitazione scientifica nazionale per professore di II fascia nel settore concorsuale 09/H1 (s.s.d. ING-INF/05).

È autore di oltre 100 pubblicazioni su riviste e convegni internazionali ed è stato membro del comitato del programma tecnico o chair di diverse conferenze nel settore della computer vision/machine learning/multimedia.

ARTICOLI SU RIVISTE INTERNAZIONALI CON IMPACT FACTOR (INDICIZZATE DA SCOPUS E/O ISI)

  1. S. Palazzo, C. Spampinato, I. Kavasidis, D. Giordano, J. Schmidt, M. Shah, Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, DOI: 10.1109/TPAMI.2020.2995909, May, 2020.

  2. G. Vecchio, S. Palazzo, D. Giordano, F. Rundo, C. Spampinato, MASK-RL: Multiagent Video Object Segmentation Framework Through Reinforcement Learning, IEEE Transactions on Neural Networks and Learning Systems, vol. 31, issue 12, pp. 5103-5115, January, 2020.

  3. C. Spampinato, S. Palazzo, P. D’Oro, D. Giordano, M. Shah, Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos, International Journal of Computer Vision, in press, DOI: https://doi.org/10.1007/s11263-019-01246-5, 2019.

  4. F. Murabito, C. Spampinato, S. Palazzo, D. Giordano, K. Pogorelov, M. Riegler, Top-down Saliency Detection Driven by Visual Classification, Computer Vision and Image Understanding, vol. 172, pp. 67-76, July, 2018.

  5. C. Spampinato, S. Palazzo, D. Giordano, M. Aldinucci, R. Leonardi, Deep Learning for Automated Skeletal Bone Age Assessment in X-Ray Images, Medical Image Analysis, vol. 37, pp. 41-51, February, 2017.

  6. C. Spampinato, S. Palazzo, D. Giordano, Gamifying Video Object Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, n. 10, pp. 1942-1958, October, 2017.

  7. D. Giordano, S. Palazzo, C. Spampinato, A diversity-based search approach to support annotation of a large fish image dataset, Multimedia Systems, vol. 22, n. 6, pp. 725-736, November, 2016.

  8. C. Spampinato, S. Palazzo, P. H. Joalland, S. Paris, H. Glotin, K. Blanc, D. Lingrand, F. Precioso, Fine-grained object recognition in underwater visual data, Multimedia Tools and Applications, vol. 75, n. 3, pp. 1701-1720, February, 2016.

  9. D. Giordano, I. Kavasidis, S. Palazzo, C. Spampinato, Nonparametric label propagation using mutual local similarity in nearest neighbors, Computer Vision and Image Understanding, vol. 131, pp. 116-127, February, 2015.

  10. B. J. Boom, J. He, S. Palazzo, P. X. Huang, C. Beyan, H. Chou, F.-P. Lin, C. Spampinato, R. B. Fisher, A research tool for long-term and continuous analysis of fish assemblage in coral-reefs using underwater camera footage, Special Issue on Multimedia in Ecology and Environment, Ecological Informatics, vol. 23, pp. 83–97, September, 2014.

  11. C. Spampinato, S. Palazzo, I. Kavasidis, A texton-based kernel density estimation approach for background modeling under extreme conditions, Computer Vision and Image Understanding, vol. 122, pp. 74-83, May, 2014.

  12. I. Kavasidis, S. Palazzo, R. Di Salvo, D. Giordano, C. Spampinato, An innovative web-based collaborative platform for video annotation, Multimedia Tools and Applications, vol. 70, n. 1, pp. 413-432, May, 2014.

  13. C. Spampinato, E. Beauxis-Aussalet, S. Palazzo, C. Beyan, J. van Ossenbruggen, J. He, B. Boom, X. Huang, A rule-based event detection system for real-life underwater domain, Machine Vision and Applications, vol. 25, n. 1, pp 99-117, May, 2014.

  14. C. Spampinato, S. Palazzo, B. Boom, J. van Ossenbruggen, I. Kavasidis, R. Di Salvo, F.-P. Lin, D. Giordano, L. Hardman, R. B. Fisher, Understanding fish behavior during typhoon events in real-life underwater environments, Multimedia Tools and Applications, vol. 70, n. 1, pp. 199-236, May, 2014.

  15. S. Palazzo, A. Murari, P. Arena, D. Mazon, Space-Varying Templates for Real-Time Applications of Cellular Nonlinear Networks to Pattern Recognition in Nuclear Fusion, IEEE Transactions on Plasma Science, vol. 41, n. 9, pp. 2516-2526, August, 2013.

  16. A. Murari, J. Vega, D. Mazon, P. Arena, T. Craciunescu, L. Gabellieri, M. Gelfusa, D. Pacella, S. Palazzo, A. Romano, JET-EFDA Contributors, Latest developments in image processing for the next generation of devices with a view on DEMO, Fusion Engineering and Design, vol. 87, n. 12, pp. 2116-2119, December 2012.

  17. S. Palazzo, A. Murari, G. Vagliasindi, P. Arena, D. Mazon, A. De Maack, and JET-EFDA Contributors, Image processing with cellular nonlinear networks implemented on field-programmable gate arrays for real-time applications in nuclear fusion, Review of Scientific Instruments, vol. 81, n. 8, August, 2010.

  18. A. Murari, J. Vega, D. Mazon, G.A. Rattà, J. Svensson, S. Palazzo, G. Vagliasindi, P. Arena, C. Boulbe, B. Faugeras, L. Fortuna, D. Moreau and JET-EFDA Contributors, Innovative signal processing and data analysis methods on JET for control in the perspective of next-step devices, Nuclear Fusion, vol. 50, n. 5, May, 2010.

 

ARTICOLI SU ATTI DI CONFERENZE (PEER-REVIEWED) INDICIZZATI ISI/SCOPUS

  1. I. Kavasidis, C. Pino, S. Palazzo, F. Rundo, D. Giordano, P. Messina, C. Spampinato, A saliency-based convolutional neural network for table and chart detection in digitized documents, International Conference on Image Analysis and Processing, Trento, Italy, September 9-13, 2019.

  2. D. Giordano, F. Murabito, S. Palazzo, C. Pino, C. Spampinato, An AI-based Framework for Supporting Large Scale Automated Analysis of Video Capsule Endoscopy, International Conference on Biomedical and Health Informatics (BHI), Chicago, Illinois, USA, May 19-22, 2019.

  3. S. Palazzo, I. Kavasidis, D. Kastaniotis, S. Dimitriadis, Recent Advances at the Brain-Driven Computer Vision Workshop 2018, Workshop on Brain-Driven Computer Vision (ECCV Proceedings), Munich, Germany, September 9, 2018.

  4. S. Palazzo, C. Spampinato, P. D'Oro, D. Giordano, M. Shah, Generating Synthetic Video Sequences by Explicitly Modeling Object Motion, International Workshop on Human Behavior Understanding (ECCV Proceedings), Munich, Germany, September 9, 2018.

  5. I. Kavasidis, S. Palazzo, C. Spampinato, D. Giordano, M. Shah, Brain2Image: Converting Brain Signals into Images, ACM International Conference on Multimedia (ACMMM), Mountain View, USA, October 23-27, 2017.

  6. C. Spampinato, S. Palazzo, I. Kavasidis, D. Giordano, M. Shah, Generative Adversarial Networks Conditioned by Brain Signals, International Conference on Computer Vision (ICCV), Venice, Italy, October 22-29, 2017.

  7. F. Murabito, S. Palazzo, C. Spampinato, D. Giordano, Generating Knowledge-Enriched Image Annotations for Fine-grained Visual Classification, International Conference on Image Analysis and Processing (ICIAP), Catania, Italy, September 11-15, 2017.

  8. F. Murabito, S. Palazzo, C. Spampinato, D. Giordano, Implicit vs. Explicit Human Feedback for Interactive Video Object Segmentation, International Conference on Image Analysis and Processing (ICIAP), Catania, Italy, September 11-15, 2017.

  9. A. Joly, H. Goeau, H. Glotin, C. Spampinato, P. Bonnet, W.-P. Vellinga, J.-C. Lombardo, R. Planquè, S. Palazzo, H. Muller, LifeCLEF 2017 Lab Overview: multimedia species identification challenges, Conference and Labs of the Evaluation Forum (CLEF), Dublin, Ireland, September 11-14, 2017.

  10. C. Spampinato, S. Palazzo, I. Kavasidis, D. Giordano, N. Souly, M. Shah, Deep learning human mind for automated visual classification, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, July 21-26, 2017.

  11. A. Joly, H. Goeau, H. Glotin, C. Spampinato, P. Bonnet, W.-P. Vellinga, J. Champ, R. Planquè, S. Palazzo, H. Muller, LifeClef 2016: Multimedia Life Species Identification Challenges, International Conference of the Cross-Language Evaluation Forum for European Languages, Evora, Portugal, September 5-8, 2016. 

  12. C. Spampinato, S. Palazzo, F. Murabito, D. Giordano, Using the eyes to see the objects, ACM International Conference on Multimedia (ACMMM), Brisbane, Australia, October, 26-30, 2015.

  13. A. Joly, H. Goeau, H. Glotin, C. Spampinato, P. Bonnet, W.-P. Vellinga, R. Planquè, A. Rauber, S. Palazzo, B. Fisher, H. Muller, LifeClef 2015: Multimedia Life Species Identification Challenges, International Conference of the CLEF Association, Toulouse, France, September 8-11, 2015.

  14. D. Giordano, I. Kavasidis, S. Palazzo, C. Spampinato, Rejecting False Positives in Video Object Segmentation, International Conference on Computer Analysis of Images and Patterns (CAIP), Valletta, Malta, September 2-4, 2015. 

  15. D. Giordano, F. Murabito, S. Palazzo, C. Spampinato, Superpixel-based video object segmentation using perceptual organization and location prior, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, USA, June 8-10, 2015. 

  16. S. Palazzo, F. Murabito, Fish Species Identification in Real-Life Underwater Images, ACM International Workshop on Multimedia Analysis for Ecological Data (MAED), Orlando, USA, November 7, 2014.

  17. C. Spampinato, S. Palazzo, PeRCeiVe Lab@UNICT at mediaEval 2014 Diverse images: Random forests for diversity-based clustering, Multimedia Benchmark Workshop, MediaEval 2014, Barcelona, Spain, October 14-17, 2014.

  18. C. Spampinato, S. Palazzo, B. Boom, R.B. Fisher, Overview of the LifeCLEF 2014 fish task, Cross Language Evaluation Forum Conference (CLEF), Sheffield; United Kingdom, September 15-18, 2014.

  19. D. Giordano, S. Palazzo, C. Spampinato, Kernel density estimation using joint spatial-color-depth data for background modeling, International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, August 24-28, 2014.

  20. S. Palazzo, C. Spampinato, D. Giordano, Large Scale Data Processing in Ecology: A Case Study on Long-Term Underwater Video Monitoring, Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Turin, Italy, February 12-14, 2014.

  21. E. Beauxis-Aussalet, S. Palazzo, G. Nadarajan, E. Arslanova, C. Spampinato, L. Hardman, A video processing and data retrieval framework for fish population monitoring, ACM International Workshop on Multimedia Analysis for Ecological Data (MAED), Barcelona, Spain, October 22, 2013.

  22. S. Palazzo, I. Kavasidis, C. Spampinato, Covariance based modeling of underwater scenes for fish detection, IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, September 15-18, 2013.

  23. C. Spampinato, S. Palazzo, Enhancing Object Detection Performance by Integrating Motion Objectness and Perceptual Organization, International Conference on Pattern Recognition (ICPR), Tsukuba Science City, Japan, November 11-15, 2012.

  24. S. Palazzo, C. Spampinato, C. Beyan, Event Detection in Underwater Domain by Exploiting Fish Trajectory Clustering, ACM International Workshop on Multimedia Analysis for Ecological Data (MAED), Nara, Japan, November 2, 2012.

  1. I. Kavasidis, S. Palazzo, Quantitative performance analysis of object detection algorithms on underwater video footage, ACM International Workshop on Multimedia Analysis for Ecological Data (MAED), Nara, Japan, November 2, 2012.

  1. A. Faro, D. Giordano, S. Palazzo, Integrating unsupervised and supervised clustering methods on a GPU platform for fast image segmentation, IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA), Istanbul, Turkey, October 15-18, 2012. 

  1. M. Aldinucci, C. Spampinato, M. Drocco, M. Torquati, S. Palazzo, A Parallel Edge Preserving Algorithm for Salt and Pepper Image Denoising, IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA), Istanbul, Turkey, October 15-18, 2012.

  2. C. Spampinato, S. Palazzo, D. Giordano, Evaluation of Tracking Algorithm Performance without Ground-Truth Data, IEEE International Conference on Image Processing (ICIP), Orlando, USA, September 30 – October 3, 2012.

  3. S. Palazzo, C. Spampinato, D. Giordano, Hidden Markov Models For Detecting Anomalous Fish Trajectories In Underwater Footage, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Santander, Spain, September 23-26, 2012.

  4. I. Kavasidis, S. Palazzo, R. Di Salvo, D. Giordano, C. Spampinato, A Semi-automatic Tool for Detection and Tracking Ground Truth Generation in Videos, International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications (VIGTA), Capri, Italy, May 21, 2012.

  5. C. Spampinato, S. Palazzo, D. Giordano, I. Kavasidis, F.P. Lin, Y.T. Lin, Covariance-based fish tracking in real-life underwater environment, International Conference on Computer Vision Theory and Applications (VISAPP 2012), Rome, Italy, February 24-26, 2012.

  6. A. Costanzo, A. Faro, S. Palazzo, Parallel Clustering of Videos to Provide Real Time Location Intelligence Services to Mobile Users, Advances in Future Computer and Control Systems, pp. 519-527, 2012.

 

CAPITOLI SU LIBRI

  1. A. Joly, H. Goeau, H. Glotin, C. Spampinato, P. Bonnet, W.-P. Vellinga, J.-C. Lombardo, R. Planquè, S. Palazzo, H. Muller, Biodiversity Information Retrieval Through Large Scale Content-Based Identification: A Long-Term Evaluation. In Information Retrieval Evaluation in a Changing World, N. Ferro, C. Peters (ed.), pp. 389-413, The Information Retrieval Series, vol. 41, Springer, Cham, 2019.

  2. D. Giordano, S. Palazzo, C. Spampinato, Fish Tracking. In Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, R. B. Fisher, Y.-H. Chen-Burger, D. Giordano, L. Hardman, F.-P. Lin (ed.), pp. 123-129, Springer International Publishing, 2016.

  3. D. Giordano, S. Palazzo, C. Spampinato, Fish Detection. In Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data, R. B. Fisher, Y.-H. Chen-Burger, D. Giordano, L. Hardman, F.-P. Lin (ed.), pp. 103-122, Springer International Publishing, 2016.

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