Zobrazeno 1 - 10
of 2 413
pro vyhledávání: '"Crupi P"'
This project, named HEnRY, aims to introduce a Multi-Agent System (MAS) into Intesa Sanpaolo. The name HEnRY summarizes the project's core principles: the Hierarchical organization of agents in a layered structure for efficient resource management; E
Externí odkaz:
http://arxiv.org/abs/2410.12720
Autor:
Bompani, Luca, Crupi, Luca, Palossi, Daniele, Baldoni, Olmo, Brunelli, Davide, Conti, Francesco, Rusci, Manuele, Benini, Luca
The codling moth pest poses a significant threat to global crop production, with potential losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in the field to record and transmit images of trapped insects to monitor
Externí odkaz:
http://arxiv.org/abs/2408.15911
Environmental, Social, and Governance (ESG) datasets are frequently plagued by significant data gaps, leading to inconsistencies in ESG ratings due to varying imputation methods. This paper explores the application of established machine learning tec
Externí odkaz:
http://arxiv.org/abs/2407.20047
Autor:
Ghirlanda, G., Nava, L., Salafia, O., Fiore, F., Campana, R., Salvaterra, R., Sanna, A., Leone, W., Evangelista, Y., Dilillo, G., Puccetti, S., Santangelo, A., Trenti, M., Guzmán, A., Hedderman, P., Amelino-Camelia, G., Barbera, M., Baroni, G., Bechini, M., Bellutti, P., Bertuccio, G., Borghi, G., Brandonisio, A., Burderi, L., Cabras, C., Chen, T., Citossi, M., Colagrossi, A., Crupi, R., De Cecio, F., Dedolli, I., Del Santo, M., Demenev, E., Di Salvo, T., Ficorella, F., Gačnik, D., Gandola, M., Gao, N., Gomboc, A., Grassi, M., Iaria, R., La Rosa, G., Cicero, U. Lo, Malcovati, P., Manca, A., Marchesini, E. J., Maselli, A., Mele, F., Nogara, P., Pepponi, G., Perri, M., Picciotto, A., Pirrotta, S., Prinetto, J., Quirino, M., Riggio, A., Řípa, J., Russo, F., Selčan, D., Silvestrini, S., Sottile, G., Thomas, M. L., Tiberia, A., Trevisan, S., Troisi, I., Tsvetkova, A., Vacchi, A., Werner, N., Zanotti, G., Zorzi, N.
Publikováno v:
A&A 689, A175 (2024)
Gamma Ray Bursts (GRBs) bridge relativistic astrophysics and multi-messenger astronomy. Space-based gamma/X-ray wide field detectors have proven essential to detect and localize the highly variable GRB prompt emission, which is also a counterpart of
Externí odkaz:
http://arxiv.org/abs/2405.17630
Autonomous nano-drones (~10 cm in diameter), thanks to their ultra-low power TinyML-based brains, are capable of coping with real-world environments. However, due to their simplified sensors and compute units, they are still far from the sense-and-ac
Externí odkaz:
http://arxiv.org/abs/2404.02567
Smart farming and precision agriculture represent game-changer technologies for efficient and sustainable agribusiness. Miniaturized palm-sized drones can act as flexible smart sensors inspecting crops, looking for early signs of potential pest outbr
Externí odkaz:
http://arxiv.org/abs/2407.00815
Autor:
Crupi, Marilena, Ficarra, Antonino
Publikováno v:
Mathematics 2024, 12(6), 912
In this paper, we give a new criterion for the Cohen-Macaulayness of vertex splittable ideals, a family of monomial ideals recently introduced by Moradi and Khosh-Ahang. Our result relies on a Betti splitting of the ideal and provides an inductive wa
Externí odkaz:
http://arxiv.org/abs/2403.14299
Autor:
Crupi, Riccardo, Regoli, Daniele, Sabatino, Alessandro Damiano, Marano, Immacolata, Brinis, Massimiliano, Albertazzi, Luca, Cirillo, Andrea, Cosentini, Andrea Claudio
Explaining outliers occurrence and mechanism of their occurrence can be extremely important in a variety of domains. Malfunctions, frauds, threats, in addition to being correctly identified, oftentimes need a valid explanation in order to effectively
Externí odkaz:
http://arxiv.org/abs/2403.10903
Relative drone-to-drone localization is a fundamental building block for any swarm operations. We address this task in the context of miniaturized nano-drones, i.e., 10cm in diameter, which show an ever-growing interest due to novel use cases enabled
Externí odkaz:
http://arxiv.org/abs/2402.13756
We propose a novel self-supervised approach for learning to visually localize robots equipped with controllable LEDs. We rely on a few training samples labeled with position ground truth and many training samples in which only the LED state is known,
Externí odkaz:
http://arxiv.org/abs/2402.09886