A.I. Tech actively participates in scientific research activities in collaboration with the University of Salerno and several other European universities (ENSICAEN, France; University of Groningen, Holland; University of Tours, France) and, in this context, hosts foreign trainees and has contributed to the following publications:

A. Greco, A. Saggese and M. Vento, “Digital Signage by Real-Time Gender Recognition From Face Images,” 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, Roma, Italy, 2020, pp. 309-313, doi: 10.1109/MetroInd4.0IoT48571.2020.9138194.

Carletti, V., Greco, A., Saggese, A., Vento M., An effective real time gender recognition system for smart cameras. J Ambient Intell Human Comput 11, 2407–2419 (2020). https://doi.org/10.1007/s12652-019-01267-5

Carletti, V., Greco, A., Saggese, A. , Vento M., An intelligent flying system for automatic detection of faults in photovoltaic plants. J Ambient Intell Human Comput 11, 2027–2040 (2020). https://doi.org/10.1007/s12652-019-01212-6

A. Greco, A. Saggese, M. Vento and V. Vigilante, “SoReNet: a novel deep network for audio surveillance applications,” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 2019, pp. 546-551, doi: 10.1109/SMC.2019.8914435.

A. Greco, C. Pironti, A. Saggese, M. Vento and V. Vigilante, “A deep learning based approach for detecting panels in photovoltaic plants”, APPIS 2020: Proceedings of the 3rd International Conference on Applications of Intelligent SystemsJanuary

V. Carletti, A. Greco, A. Saggese and M. Vento, “Multi-Object Tracking by Flying Cameras Based on a Forward-Backward Interaction,” in IEEE Access, vol. 6, pp. 43905-43919, 2018, doi: 10.1109/ACCESS.2018.2864672.

V. Carletti, A. Greco, A. Saggese, M. Vento and V. Vigilante, “A Wearable Embedded System for Detecting Accidents while Running”, VISAPP 2018 – International Conference on Computer Vision Theory and Applications

A. Arenella, A. Greco, A. Saggese, M. Vento, “Real Time Fault Detection in Photovoltaic Cells by Cameras on Drones”, ICIAR 2017 – Image Analysis and Recognition

Luc Brun, Gennaro Percannella, Alessia Saggese, Mario Vento, Action recognition by using kernels on aclets sequences, Computer Vision and Image Understanding, Volume 144, 2016

Luca Del Pizzo, Pasquale Foggia, Antonio Greco, Gennaro Percannella, Mario Vento, Counting people by RGB or depth overhead cameras, Pattern Recognition Letters, Volume 81, 2016,

Pasquale Foggia, Nicolai Petkov, Alessia Saggese, Nicola Strisciuglio, Mario Vento, Reliable detection of audio events in highly noisy environments, Pattern Recognition Letters, Volume 65, 2015

V. Carletti, P. Foggia, A. Greco, A. Saggese and M. Vento, “Automatic detection of long term parked cars,” 2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Karlsruhe, 2015, pp. 1-6, doi: 10.1109/AVSS.2015.7301722.

L. Del Pizzo, P. Foggia, A. Greco, G. Percannella and M. Vento, “A versatile and effective method for counting people on either RGB or depth overhead cameras,” 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Turin, 2015, pp. 1-6, doi: 10.1109/ICMEW.2015.7169795.

Giovanni Acampora, Pasquale Foggia, Alessia Saggese, Mario Vento, A hierarchical neuro-fuzzy architecture for human behavior analysis, Information Sciences, Volume 310, 2015

P. Foggia, A. Greco, A. Saggese, M. Vento, A method for detection long term left baggage based on Heat Map, VISAPP 2015 – International Conference on Computer Vision Theory and Applications

L. Brun, P. Foggia, A. Saggese, M. Vento, Recognition of Human Actions using Edit Distance on Aclet Strings, VISAPP 2015 – International Conference on Computer Vision Theory and Applications

A. d’Acierno, A. Saggese and M. Vento, “Designing Huge Repositories of Moving Vehicles Trajectories for Efficient Extraction of Semantic Data,” in IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 4, pp. 2038-2049, Aug. 2015, doi: 10.1109/TITS.2015.2390652.

P. Foggia, A. Saggese and M. Vento, “Real-Time Fire Detection for Video-Surveillance Applications Using a Combination of Experts Based on Color, Shape, and Motion,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 9, pp. 1545-1556, Sept. 2015, doi: 10.1109/TCSVT.2015.2392531.

Di Lascio R., Greco A., Saggese A., Vento M. (2014) Improving Fire Detection Reliability by a Combination of Videoanalytics. In: Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science, vol 8814. Springer, Cham.

Vincenzo Carletti, Luca Del Pizzo, Gennaro Percannella, Mario Vento, Foreground Detection Optimization for SoCs embedded on Smart Cameras, ICDSC ’14, Proceedings of the International Conference on Distributed Smart CamerasNovember 2014

L. Brun, B. Cappellania, A. Saggese and M. Vento, “Detection of anomalous driving behaviors by unsupervised learning of graphs,” 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Seoul, 2014, pp. 405-410, doi: 10.1109/AVSS.2014.6918702.

L. Brun, G. Percannella, A. Saggese and M. Vento, “HAck: A system for the recognition of human actions by kernels of visual strings,” 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Seoul, 2014, pp. 142-147, doi: 10.1109/AVSS.2014.6918658.

L. Brun, A. Saggese and M. Vento, “Dynamic Scene Understanding for Behavior Analysis Based on String Kernels,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 10, pp. 1669-1681, Oct. 2014, doi: 10.1109/TCSVT.2014.2302521.

Conte, D., Foggia, P., Percannella, G. et al. Counting moving persons in crowded scenes. Machine Vision and Applications 24, 1029–1042 (2013). https://doi.org/10.1007/s00138-013-0491-3

D. Conte, R. Di Lascio, P. Foggia, G. Percannella, M. Vento, Pupil Localization by a Template Matching Method, VISAPP 2013 – International Conference on Computer Vision Theory and Applications

P. Foggia, G. Percannella, A. Saggese and M. Vento, “Recognizing Human Actions by a Bag of Visual Words,” 2013 IEEE International Conference on Systems, Man, and Cybernetics, Manchester, 2013, pp. 2910-2915, doi: 10.1109/SMC.2013.496.

Carletti V., Foggia P., Percannella G., Saggese A., Vento M. (2013) Recognition of Human Actions from RGB-D Videos Using a Reject Option. In: Petrosino A., Maddalena L., Pala P. (eds) New Trends in Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8158. Springer, Berlin, Heidelberg.

Rosario Di Lascio, Pasquale Foggia, Gennaro Percannella, Alessia Saggese, Mario Vento, A real time algorithm for people tracking using contextual reasoning, Computer Vision and Image Understanding, Volume 117, Issue 8, 2013

P. Foggia, G. Percannella, A. Saggese and M. Vento, “Real-time tracking of single people and groups simultaneously by contextual graph-based reasoning dealing complex occlusions,” 2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS), Clearwater, FL, 2013, pp. 29-36, doi: 10.1109/PETS.2013.6523792.

Di Lascio R., Foggia P., Saggese A., Vento M. (2013) A Robust People Tracking Algorithm Using Contextual Reasoning for Recovering Detection Errors. In: Csurka G., Kraus M., Laramee R.S., Richard P., Braz J. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Application. Communications in Computer and Information Science, vol 359

Antonio d’Acierno, Marco Leone, Alessia Saggese and Mario Vento, An Efficient Strategy for Spatio-temporal Data Indexing and Retrieval, KDIR 2012 – International Conference on Knowledge Discovery and Information Retrieval

L. Brun, A. Saggese and M. Vento, “A Clustering Algorithm of Trajectories for Behaviour Understanding Based on String Kernels,” 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems, Naples, 2012, pp. 267-274, doi: 10.1109/SITIS.2012.47.

A. d’Acierno, M. Leone, A. Saggese and M. Vento, “A system for storing and retrieving huge amount of trajectory data, allowing spatio-temporal dynamic queries,” 2012 15th International IEEE Conference on Intelligent Transportation Systems, Anchorage, AK, 2012, pp. 989-994, doi: 10.1109/ITSC.2012.6338684.

Rosario Di Lascio, Pasquale Foggia, Alessia Saggese and Mario Vento, Tracking interacting objects in complex situations by using contextual reasoning, VISAPP 2012 – International Conference on Computer Vision Theory and Applications

D. Conte, P. Foggia, G. Percannella and M. Vento, “Removing Object Reflections in Videos by Global Optimization,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 11, pp. 1623-1633, Nov. 2012, doi: 10.1109/TCSVT.2012.2202187.

Percannella G., Vento M. (2011) A Self-trainable System for Moving People Counting by Scene Partitioning. In: Kamel M., Campilho A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754

D. Conte, P. Foggia, G. Percannella and M. Vento, “A Method Based on the Indirect Approach for Counting People in Crowded Scenes,” 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, Boston, MA, 2010, pp. 111-118, doi: 10.1109/AVSS.2010.86.

D. Conte, P. Foggia, G. Percannella and M. Vento, “Performance Evaluation of a People Tracking System on PETS2009 Database,” 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, Boston, MA, 2010, pp. 119-126, doi: 10.1109/AVSS.2010.87.